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ORCIDJames Zou 0001
James Y. Zou
Person information
- affiliation: Stanford University, Department of Electrical Engineering, CA, USA
- affiliation: Harvard University, School of Engineering and Applied Sciences, Cambridge, MA, USA
Other persons with the same name
- James Zou — disambiguation page
- James Zou 0002 — Microsoft Research, One Memorial Dr, Cambridge, MA, USA
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2020 – today
- 2025
[j37]Mert Yüksekgönül, Federico Bianchi, Joseph Boen, Sheng Liu, Pan Lu, Zhi Huang, Carlos Guestrin, James Zou:
Optimizing generative AI by backpropagating language model feedback. Nat. 639(8055): 609-616 (2025)- [i182]Shirley Wu, Michel Galley, Baolin Peng, Hao Cheng, Gavin Li, Yao Dou, Weixin Cai, James Zou, Jure Leskovec, Jianfeng Gao:
CollabLLM: From Passive Responders to Active Collaborators. CoRR abs/2502.00640 (2025) - [i181]Wanjia Zhao, Mert Yüksekgönül, Shirley Wu, James Zou:
SiriuS: Self-improving Multi-agent Systems via Bootstrapped Reasoning. CoRR abs/2502.04780 (2025) - [i180]Pan Lu, Bowen Chen, Sheng Liu, Rahul Thapa, Joseph Boen, James Zou:
OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning. CoRR abs/2502.11271 (2025) - [i179]Lingjiao Chen, Jared Quincy Davis, Boris Hanin, Peter Bailis, Matei Zaharia, James Zou, Ion Stoica:
Optimizing Model Selection for Compound AI Systems. CoRR abs/2502.14815 (2025) - [i178]Avanika Narayan, Dan Biderman, Sabri Eyuboglu, Avner May, Scott W. Linderman, James Zou, Christopher Ré:
Minions: Cost-efficient Collaboration Between On-device and Cloud Language Models. CoRR abs/2502.15964 (2025) - [i177]Yijia Xiao, Wanjia Zhao, Junkai Zhang, Yiqiao Jin, Han Zhang, Zhicheng Ren, Renliang Sun, Haixin Wang, Guancheng Wan, Pan Lu, Xiao Luo, Yu Zhang, James Zou, Yizhou Sun, Wei Wang:
Protein Large Language Models: A Comprehensive Survey. CoRR abs/2502.17504 (2025) - [i176]Meghana Arakkal Rajeev, Rajkumar Ramamurthy, Prapti Trivedi, Vikas Yadav, Oluwanifemi Bamgbose, Sathwik Tejaswi Madhusudhan, James Zou, Nazneen Rajani:
Cats Confuse Reasoning LLM: Query Agnostic Adversarial Triggers for Reasoning Models. CoRR abs/2503.01781 (2025) - 2024
- [j36]Kyle Swanson
, Parker Walther, Jeremy Leitz, Souhrid Mukherjee, Joseph C. Wu, Rabindra V. Shivnaraine, James Zou:
ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries. Bioinform. 40(7) (2024) - [j35]Eric D. Sun, Rong Ma, James Zou:
SPRITE: improving spatial gene expression imputation with gene and cell networks. Bioinform. 40(Supplement_1): i521-i528 (2024) - [j34]Kyle Swanson, Gary Liu, Denise B. Catacutan, Autumn Arnold, James Zou, Jonathan M. Stokes:
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics. Nat. Mac. Intell. 6(3): 338-353 (2024) - [j33]Weixin Liang, Nazneen Rajani, Xinyu Yang, Ezinwanne Ozoani, Eric Wu, Yiqun Chen, Daniel Scott Smith, James Zou:
Systematic analysis of 32,111 AI model cards characterizes documentation practice in AI. Nat. Mac. Intell. 6(7): 744-753 (2024) - [j32]Rohaid Ali, Ian D. Connolly, Oliver Y. Tang, Fatima N. Mirza, Benjamin Johnston, Hael F. Abdulrazeq, Paul F. Galamaga, Tiffany J. Libby, Neel R. Sodha, Michael W. Groff, Ziya L. Gokaslan, Albert E. Telfeian, John H. Shin, Wael F. Asaad, James Zou, Curtis E. Doberstein:
Bridging the literacy gap for surgical consents: an AI-human expert collaborative approach. npj Digit. Medicine 7(1) (2024) - [j31]Rohaid Ali, Ian D. Connolly, Oliver Y. Tang, Fatima N. Mirza, Benjamin Johnston, Hael F. Abdulrazeq, Rachel K. Lim, Paul F. Galamaga, Tiffany J. Libby, Neel R. Sodha, Michael W. Groff, Ziya L. Gokaslan, Albert E. Telfeian, John H. Shin, Wael F. Asaad, James Zou, Curtis E. Doberstein:
Author Correction: Bridging the literacy gap for surgical consents: an AI-human expert collaborative approach. npj Digit. Medicine 7(1) (2024) - [j30]Zachary Izzo, Jinsung Yoon, Sercan Ö. Arik, James Zou:
Provable Membership Inference Privacy. Trans. Mach. Learn. Res. 2024 (2024) - [c133]Sabri Eyuboglu, Karan Goel, Arjun D. Desai, Lingjiao Chen, Mathew Monfort, Christopher Ré, James Zou:
Model ChangeLists: Characterizing Updates to ML Models. FAccT 2024: 2432-2453 - [c132]Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, James Zou:
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions. ICLR 2024 - [c131]Simran Arora, Sabri Eyuboglu, Aman Timalsina, Isys Johnson, Michael Poli, James Zou, Atri Rudra, Christopher Ré:
Zoology: Measuring and Improving Recall in Efficient Language Models. ICLR 2024 - [c130]Yongchan Kwon, Eric Wu, Kevin Wu, James Zou:
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models. ICLR 2024 - [c129]Xinyu Yang, Weixin Liang, James Zou:
Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on HuggingFace. ICLR 2024 - [c128]Federico Bianchi, Patrick John Chia, Mert Yüksekgönül, Jacopo Tagliabue, Dan Jurafsky, James Zou:
How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis. ICML 2024 - [c127]Simran Arora, Sabri Eyuboglu, Michael Zhang, Aman Timalsina, Silas Alberti, James Zou, Atri Rudra, Christopher Ré:
Simple linear attention language models balance the recall-throughput tradeoff. ICML 2024 - [c126]Ian Connick Covert, Wenlong Ji, Tatsunori Hashimoto, James Zou:
Scaling Laws for the Value of Individual Data Points in Machine Learning. ICML 2024 - [c125]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c124]Weixin Liang, Zachary Izzo, Yaohui Zhang, Haley Lepp, Hancheng Cao, Xuandong Zhao, Lingjiao Chen, Haotian Ye, Sheng Liu, Zhi Huang, Daniel A. McFarland, James Y. Zou:
Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews. ICML 2024 - [c123]Haowei Lin, Baizhou Huang, Haotian Ye, Qinyu Chen, Zihao Wang, Sujian Li, Jianzhu Ma, Xiaojun Wan, James Zou, Yitao Liang:
Selecting Large Language Model to Fine-tune via Rectified Scaling Law. ICML 2024 - [c122]Sheng Liu, Haotian Ye, Lei Xing, James Y. Zou:
In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering. ICML 2024 - [c121]Gautam Machiraju, Alexander Derry, Arjun D. Desai, Neel Guha, Amir-Hossein Karimi, James Zou, Russ B. Altman, Christopher Ré, Parag Mallick:
Prospector Heads: Generalized Feature Attribution for Large Models & Data. ICML 2024 - [c120]Rahul Thapa, Bryan He, Magnus Ruud Kjær, Hyatt E. Moore IV, Gauri Ganjoo, Emmanuel Mignot, James Zou:
SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals. ICML 2024 - [c119]Kailas Vodrahalli, James Zou:
ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations. ICML 2024 - [c118]Jiachen T. Wang, Tianji Yang, James Zou, Yongchan Kwon, Ruoxi Jia:
Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits. ICML 2024 - [c117]Jiachen Zhao, Zhun Deng, David Madras, James Zou, Mengye Ren:
Learning and Forgetting Unsafe Examples in Large Language Models. ICML 2024 - [c116]Lingjiao Chen, Jared Quincy Davis, Boris Hanin, Peter Bailis, Ion Stoica, Matei A. Zaharia, James Y. Zou:
Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems. NeurIPS 2024 - [c115]Ian Covert, Chanwoo Kim, Su-In Lee, James Y. Zou, Tatsunori B. Hashimoto:
Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution. NeurIPS 2024 - [c114]Yihe Deng, Pan Lu, Fan Yin, Ziniu Hu, Sheng Shen, Quanquan Gu, James Y. Zou, Kai-Wei Chang, Wei Wang:
Enhancing Large Vision Language Models with Self-Training on Image Comprehension. NeurIPS 2024 - [c113]Jacob Silberg, Kyle Swanson, Elana Simon, Angela Zhang, Zaniar Ghazizadeh, Scott Ogden, Hisham Hamadeh, James Y. Zou:
UniTox: Leveraging LLMs to Curate a Unified Dataset of Drug-Induced Toxicity from FDA Labels. NeurIPS 2024 - [c112]Chau Tran, Duy M. H. Nguyen, Manh-Duy Nguyen, TrungTin Nguyen, Ngan Le, Pengtao Xie, Daniel Sonntag, James Y. Zou, Binh Nguyen, Mathias Niepert:
Accelerating Transformers with Spectrum-Preserving Token Merging. NeurIPS 2024 - [c111]Shirley Wu, Kaidi Cao, Bruno Ribeiro, James Y. Zou, Jure Leskovec:
GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts. NeurIPS 2024 - [c110]Kevin Wu, Eric Wu, James Y. Zou:
ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidence. NeurIPS 2024 - [c109]Shirley Wu, Shiyu Zhao, Qian Huang, Kexin Huang, Michihiro Yasunaga, Kaidi Cao, Vassilis N. Ioannidis, Karthik Subbian, Jure Leskovec, James Y. Zou:
AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning. NeurIPS 2024 - [c108]Shirley Wu, Shiyu Zhao, Michihiro Yasunaga, Kexin Huang, Kaidi Cao, Qian Huang, Vassilis N. Ioannidis, Karthik Subbian, James Y. Zou, Jure Leskovec:
STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases. NeurIPS 2024 - [c107]Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, Zongyuan Ge, Gang Li, James Y. Zou, Huaxiu Yao:
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models. NeurIPS 2024 - [c106]Haotian Ye, Haowei Lin, Jiaqi Han, Minkai Xu, Sheng Liu, Yitao Liang, Jianzhu Ma, James Y. Zou, Stefano Ermon:
TFG: Unified Training-Free Guidance for Diffusion Models. NeurIPS 2024 - [i175]Haonan Wang, James Zou, Michael Mozer, Anirudh Goyal, Alex Lamb, Linjun Zhang, Weijie J. Su, Zhun Deng, Michael Qizhe Xie, Hannah Brown, Kenji Kawaguchi:
Can AI Be as Creative as Humans? CoRR abs/2401.01623 (2024) - [i174]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i173]Xinyu Yang, Weixin Liang, James Zou:
Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on Hugging Face. CoRR abs/2401.13822 (2024) - [i172]Ian Covert, Chanwoo Kim, Su-In Lee, James Zou, Tatsunori Hashimoto:
Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution. CoRR abs/2401.15866 (2024) - [i171]Kevin Wu, Eric Wu, Ally Cassasola, Angela Zhang, Kevin Wei, Teresa Nguyen, Sith Riantawan, Patricia Shi Riantawan, Daniel E. Ho, James Zou:
How well do LLMs cite relevant medical references? An evaluation framework and analyses. CoRR abs/2402.02008 (2024) - [i170]Haowei Lin, Baizhou Huang, Haotian Ye, Qinyu Chen, Zihao Wang, Sujian Li, Jianzhu Ma, Xiaojun Wan, James Zou, Yitao Liang:
Selecting Large Language Model to Fine-tune via Rectified Scaling Law. CoRR abs/2402.02314 (2024) - [i169]Weixin Liang, Nazneen Rajani, Xinyu Yang, Ezinwanne Ozoani, Eric Wu, Yiqun Chen, Daniel Scott Smith, James Zou:
What's documented in AI? Systematic Analysis of 32K AI Model Cards. CoRR abs/2402.05160 (2024) - [i168]Federico Bianchi, Patrick John Chia, Mert Yüksekgönül, Jacopo Tagliabue, Dan Jurafsky, James Zou:
How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis. CoRR abs/2402.05863 (2024) - [i167]Gautam Machiraju, Alexander Derry, Arjun D. Desai, Neel Guha, Amir-Hossein Karimi, James Zou, Russ B. Altman, Christopher Ré, Parag Mallick:
Prospector Heads: Generalized Feature Attribution for Large Models & Data. CoRR abs/2402.11729 (2024) - [i166]Federico Bianchi, James Zou:
Large Language Models are Vulnerable to Bait-and-Switch Attacks for Generating Harmful Content. CoRR abs/2402.13926 (2024) - [i165]Simran Arora, Sabri Eyuboglu, Michael Zhang, Aman Timalsina, Silas Alberti, Dylan Zinsley, James Zou, Atri Rudra, Christopher Ré:
Simple linear attention language models balance the recall-throughput tradeoff. CoRR abs/2402.18668 (2024) - [i164]Lingjiao Chen, Jared Quincy Davis, Boris Hanin, Peter Bailis, Ion Stoica, Matei Zaharia, James Zou:
Are More LLM Calls All You Need? Towards Scaling Laws of Compound Inference Systems. CoRR abs/2403.02419 (2024) - [i163]Weixin Liang, Zachary Izzo, Yaohui Zhang, Haley Lepp, Hancheng Cao, Xuandong Zhao, Lingjiao Chen, Haotian Ye, Sheng Liu, Zhi Huang, Daniel A. McFarland, James Y. Zou:
Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews. CoRR abs/2403.07183 (2024) - [i162]Weixin Liang, Yaohui Zhang, Zhengxuan Wu, Haley Lepp, Wenlong Ji, Xuandong Zhao, Hancheng Cao, Sheng Liu, Siyu He, Zhi Huang, Diyi Yang, Christopher Potts, Christopher D. Manning, James Y. Zou:
Mapping the Increasing Use of LLMs in Scientific Papers. CoRR abs/2404.01268 (2024) - [i161]Kevin Wu, Eric Wu, James Zou:
How faithful are RAG models? Quantifying the tug-of-war between RAG and LLMs' internal prior. CoRR abs/2404.10198 (2024) - [i160]Yuchi Liu, Lei Wang, Yuli Zou, James Zou, Liang Zheng:
Optimizing Calibration by Gaining Aware of Prediction Correctness. CoRR abs/2404.13016 (2024) - [i159]Shirley Wu, Shiyu Zhao, Michihiro Yasunaga, Kexin Huang, Kaidi Cao, Qian Huang, Vassilis N. Ioannidis, Karthik Subbian, James Zou, Jure Leskovec:
STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases. CoRR abs/2404.13207 (2024) - [i158]Jiachen T. Wang, Tianji Yang, James Zou, Yongchan Kwon, Ruoxi Jia:
Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits. CoRR abs/2405.03875 (2024) - [i157]Hoai-Chau Tran, Duy M. H. Nguyen, Duy M. Nguyen, TrungTin Nguyen, Ngan Le, Pengtao Xie, Daniel Sonntag, James Y. Zou, Binh T. Nguyen, Mathias Niepert:
Accelerating Transformers with Spectrum-Preserving Token Merging. CoRR abs/2405.16148 (2024) - [i156]Rahul Thapa, Bryan He, Magnus Ruud Kjær, Hyatt E. Moore IV, Gauri Ganjoo, Emmanuel Mignot, James Zou:
SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals. CoRR abs/2405.17766 (2024) - [i155]Shuran Zheng, Yongchan Kwon, Xuan Qi, James Zou:
Truthful Dataset Valuation by Pointwise Mutual Information. CoRR abs/2405.18253 (2024) - [i154]Yihe Deng, Pan Lu, Fan Yin, Ziniu Hu, Sheng Shen, James Zou, Kai-Wei Chang, Wei Wang:
Enhancing Large Vision Language Models with Self-Training on Image Comprehension. CoRR abs/2405.19716 (2024) - [i153]Ian Covert, Wenlong Ji, Tatsunori Hashimoto, James Zou:
Scaling Laws for the Value of Individual Data Points in Machine Learning. CoRR abs/2405.20456 (2024) - [i152]Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, Zongyuan Ge, Gang Li, James Zou, Huaxiu Yao:
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models. CoRR abs/2406.06007 (2024) - [i151]Mert Yüksekgönül, Federico Bianchi, Joseph Boen, Sheng Liu, Zhi Huang, Carlos Guestrin, James Zou:
TextGrad: Automatic "Differentiation" via Text. CoRR abs/2406.07496 (2024) - [i150]Shirley Wu, Shiyu Zhao, Qian Huang, Kexin Huang, Michihiro Yasunaga, Kaidi Cao, Vassilis N. Ioannidis, Karthik Subbian, Jure Leskovec, James Zou:
AvaTaR: Optimizing LLM Agents for Tool-Assisted Knowledge Retrieval. CoRR abs/2406.11200 (2024) - [i149]Sheng Liu, Oscar Pastor-Serrano, Yizheng Chen, Matthew Gopaulchan, Weixing Liang, Mark Buyyounouski, Erqi Pollom, Quynh-Thu Le, Michael Gensheimer, Peng Dong, Yong Yang, James Zou, Lei Xing:
Automated radiotherapy treatment planning guided by GPT-4Vision. CoRR abs/2406.15609 (2024) - [i148]Yuan Li, Yue Huang, Hongyi Wang, Xiangliang Zhang, James Zou, Lichao Sun:
Quantifying AI Psychology: A Psychometrics Benchmark for Large Language Models. CoRR abs/2406.17675 (2024) - [i147]Kevin Wu, Eric Wu, Kit T. Rodolfa, Daniel E. Ho, James Zou:
Regulating AI Adaptation: An Analysis of AI Medical Device Updates. CoRR abs/2407.16900 (2024) - [i146]Yunfei Xie, Ce Zhou, Lang Gao, Juncheng Wu, Xianhang Li, Hong-Yu Zhou, Sheng Liu, Lei Xing, James Zou, Cihang Xie, Yuyin Zhou:
MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine. CoRR abs/2408.02900 (2024) - [i145]Li Zhang, Basu Jindal, Ahmed Alaa, Robert Weinreb, David Wilson, Eran Segal, James Zou, Pengtao Xie:
Generative AI Enables Medical Image Segmentation in Ultra Low-Data Regimes. CoRR abs/2408.17421 (2024) - [i144]Haotian Ye, Haowei Lin, Jiaqi Han, Minkai Xu, Sheng Liu, Yitao Liang, Jianzhu Ma, James Zou, Stefano Ermon:
TFG: Unified Training-Free Guidance for Diffusion Models. CoRR abs/2409.15761 (2024) - [i143]Prapti Trivedi, Aditya Gulati, Oliver Molenschot, Meghana Arakkal Rajeev, Rajkumar Ramamurthy, Keith Stevens, Tanveesh Singh Chaudhery, Jahnavi Jambholkar, James Zou, Nazneen Rajani:
Self-rationalization improves LLM as a fine-grained judge. CoRR abs/2410.05495 (2024) - [i142]Ian Covert, Tony Sun, James Zou, Tatsunori Hashimoto:
Locality Alignment Improves Vision-Language Models. CoRR abs/2410.11087 (2024) - [i141]Peng Xia, Kangyu Zhu, Haoran Li, Tianze Wang, Weijia Shi, Sheng Wang, Linjun Zhang, James Zou, Huaxiu Yao:
MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models. CoRR abs/2410.13085 (2024) - [i140]Sheng Liu, Haotian Ye, Lei Xing, James Zou:
Reducing Hallucinations in Vision-Language Models via Latent Space Steering. CoRR abs/2410.15778 (2024) - [i139]Mirac Suzgun, Tayfun Gur, Federico Bianchi, Daniel E. Ho, Thomas Icard, Dan Jurafsky, James Zou:
Belief in the Machine: Investigating Epistemological Blind Spots of Language Models. CoRR abs/2410.21195 (2024) - [i138]Fan Nie, Xiaotian Hou, Shuhang Lin, James Zou, Huaxiu Yao, Linjun Zhang:
FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees. CoRR abs/2411.02603 (2024) - [i137]Rajkumar Ramamurthy, Meghana Arakkal Rajeev, Oliver Molenschot, James Zou, Nazneen Rajani:
VERITAS: A Unified Approach to Reliability Evaluation. CoRR abs/2411.03300 (2024) - [i136]Eric Wu, Kevin Wu, James Zou:
FineTuneBench: How well do commercial fine-tuning APIs infuse knowledge into LLMs? CoRR abs/2411.05059 (2024) - [i135]Jiayao Zhang, Yuran Bi, Mengye Cheng, Jinfei Liu, Kui Ren, Qiheng Sun, Yihang Wu, Yang Cao, Raul Castro Fernandez, Haifeng Xu, Ruoxi Jia, Yongchan Kwon, Jian Pei, Jiachen T. Wang, Haocheng Xia, Li Xiong, Xiaohui Yu, James Zou:
A Survey on Data Markets. CoRR abs/2411.07267 (2024) - [i134]Jiachen T. Wang, Dawn Song, James Zou, Prateek Mittal, Ruoxi Jia:
Capturing the Temporal Dependence of Training Data Influence. CoRR abs/2412.09538 (2024) - 2023
- [j29]Kevin E. Wu, James Y. Zou, Howard Chang:
Machine learning modeling of RNA structures: methods, challenges and future perspectives. Briefings Bioinform. 24(4) (2023) - [j28]Wenlong Ji, Zhun Deng, Ryumei Nakada, James Zou, Linjun Zhang:
The Power of Contrast for Feature Learning: A Theoretical Analysis. J. Mach. Learn. Res. 24: 330:1-330:78 (2023) - [j27]Xiaowei Xu, Qianjun Jia, Haiyun Yuan, Hailong Qiu, Yuhao Dong, Wen Xie, Zeyang Yao, Jiawei Zhang, Zhiqaing Nie, Xiaomeng Li, Yiyu Shi, James Y. Zou, Meiping Huang, Jian Zhuang:
A clinically applicable AI system for diagnosis of congenital heart diseases based on computed tomography images. Medical Image Anal. 90: 102953 (2023) - [j26]Eric D. Sun, Rong Ma, James Zou:
Dynamic visualization of high-dimensional data. Nat. Comput. Sci. 3(1): 86-100 (2023) - [j25]Andre Esteva, Jean Feng, Douwe van der Wal, Shih-Cheng Huang, Jeffry P. Simko, Sandy Devries, Emmalyn Chen, Edward M. Schaeffer, Todd M. Morgan, Yilun Sun, Amirata Ghorbani, Nikhil Naik, Dhruv Nathawani, Richard Socher, Jeff M. Michalski, Mack Roach, Thomas M. Pisansky, Jedidiah M. Monson, Farah Naz, James Wallace, Michelle J. Ferguson, Jean-Paul Bahary, James Zou, Matthew P. Lungren, Serena Yeung, Ashley E. Ross, Michael J. Kucharczyk, Luis Souhami, Leslie Ballas, Christopher A. Peters, Sandy Liu, Alexander G. Balogh, Pamela D. Randolph-Jackson, David L. Schwartz, Michael R. Girvigian, Naoyuki G. Saito, Adam Raben, Rachel A. Rabinovitch, Khalil Katato, Howard M. Sandler, Phuoc T. Tran, Daniel E. Spratt, Stephanie Pugh, Felix Y. Feng, Osama Mohamad:
Author Correction: Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials. npj Digit. Medicine 6 (2023) - [j24]J. Weston Hughes, James E. Tooley, Jessica Torres Soto, Anna Ostropolets, Tim Poterucha, Matthew Christensen, Neal Yuan, Ben Ehlert, Dhamanpreet Kaur, Guson Kang, Albert J. Rogers, Sanjiv M. Narayan, Pierre A. Elias, David Ouyang, Euan A. Ashley, James Zou, Marco V. Perez:
A deep learning-based electrocardiogram risk score for long term cardiovascular death and disease. npj Digit. Medicine 6 (2023) - [j23]Girmaw Abebe Tadesse, Celia Cintas, Kush R. Varshney, Peter W. J. Staar, Chinyere Agunwa, Skyler Speakman, Justin Jia, Elizabeth E. Bailey, Ademide Adelekun, Jules Lipoff, Ginikanwa Onyekaba, Jenna C. Lester, Veronica Rotemberg, James Zou, Roxana Daneshjou:
Skin Tone Analysis for Representation in Educational Materials (STAR-ED) using machine learning. npj Digit. Medicine 6 (2023) - [j22]Weixin Liang, Mert Yüksekgönül, Yining Mao, Eric Wu, James Zou:
GPT detectors are biased against non-native English writers. Patterns 4(7): 100779 (2023) - [j21]Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew M. Dai, Andrew La, Andrew K. Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakas, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartlomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, Cèsar Ferri Ramírez, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Chris Waites, Christian Voigt, Christopher D. Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodolà, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A. Chi, Ethan Dyer, Ethan J. Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, François Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Wang, Gonzalo Jaimovitch-López, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Shevlin, Hinrich Schütze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B. Simon, James Koppel, James Zheng, James Zou, Jan Kocon, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse H. Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, José Hernández-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh D. Dhole, Kevin Gimpel, Kevin Omondi, Kory W. Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros Colón, Luke Metz, Lütfi Kerem Senel, Maarten Bosma, Maarten Sap, Maartje ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, María José Ramírez-Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L. Leavitt, Matthias Hagen, Mátyás Schubert, Medina Baitemirova, Melody Arnaud, Melvin McElrath, Michael A. Yee, Michael Cohen, Michael Gu, Michael I. Ivanitskiy, Michael Starritt, Michael Strube, Michal Swedrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T., Nanyun Peng, Nathan A. Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Milkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan LeBras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Ruslan Salakhutdinov, Ryan Chi, Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel S. Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima (Shammie) Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven T. Piantadosi, Stuart M. Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsu Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay V. Ramasesh, Vinay Uday Prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, Zirui Wang, Ziyi Wu:
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. Trans. Mach. Learn. Res. 2023 (2023) - [c105]Lingjiao Chen, Zhihua Jin, Sabri Eyuboglu, Huamin Qu, Christopher Ré, Matei Zaharia, James Zou:
HAPI Explorer: Comprehension, Discovery, and Explanation on History of ML APIs. AAAI 2023: 16416-16418 - [c104]Yuhui Zhang, Michihiro Yasunaga, Zhengping Zhou, Jeff Z. HaoChen, James Zou, Percy Liang, Serena Yeung:
Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models. ACL (Findings) 2023: 7479-7498 - [c103]Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang:
Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. AISTATS 2023: 4348-4380 - [c102]Haotian Ye, James Zou, Linjun Zhang:
Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise. AISTATS 2023: 8968-8990 - [c101]Kevin Wu, Dominik Dahlem, Christopher Hane, Eran Halperin, James Zou:
Collecting data when missingness is unknown: a method for improving model performance given under-reporting in patient populations. CHIL 2023: 229-242 - [c100]Kailas Vodrahalli, Gregory D. Lyng, Brian L. Hill, Kimmo Kärkkäinen, Jeffrey Hertzberg, James Zou, Eran Halperin:
Understanding and Predicting the Effect of Environmental Factors on People with Type 2 Diabetes. CHIL 2023: 545-555 - [c99]Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, Aylin Caliskan:
Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale. FAccT 2023: 1493-1504 - [c98]Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou:
FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. ICLR 2023 - [c97]Puheng Li, James Zou, Linjun Zhang:
FaiREE: fair classification with finite-sample and distribution-free guarantee. ICLR 2023 - [c96]Mert Yüksekgönül, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, James Zou:
When and Why Vision-Language Models Behave like Bags-Of-Words, and What to Do About It? ICLR 2023 - [c95]Mert Yüksekgönül, Maggie Wang, James Zou:
Post-hoc Concept Bottleneck Models. ICLR 2023 - [c94]Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung:
Diagnosing and Rectifying Vision Models using Language. ICLR 2023 - [c93]Zachary Izzo, Ruishan Liu, James Zou:
Data-Driven Subgroup Identification for Linear Regression. ICML 2023: 14531-14552 - [c92]Yongchan Kwon, James Zou:
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value. ICML 2023: 18135-18152 - [c91]Weixin Liang, Yining Mao, Yongchan Kwon, Xinyu Yang, James Zou:
Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations. ICML 2023: 20706-20724 - [c90]Shirley Wu, Mert Yüksekgönül, Linjun Zhang, James Zou:
Discover and Cure: Concept-aware Mitigation of Spurious Correlation. ICML 2023: 37765-37786 - [c89]Jennifer Yu, Zhenqin Wu, Aaron T. Mayer, Alexandro Trevino, James Zou:
A Multi-Granularity Approach to Similarity Search in Multiplexed Immunofluorescence Images. MLCB 2023: 135-147 - [c88]Kevin E. Wu, Kathryn Yost, Bence Daniel, Julia A. Belk, Yu Xia, Takeshi Egawa, Ansuman Satpathy, Howard Chang, James Zou:
TCR-BERT: learning the grammar of T-cell receptors for flexible antigen-binding analyses. MLCB 2023: 194-229 - [c87]Yiqun T. Chen, James Y. Zou:
TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter. NeurIPS 2023 - [c86]Kevin Fu Jiang, Weixin Liang, James Y. Zou, Yongchan Kwon:
OpenDataVal: a Unified Benchmark for Data Valuation. NeurIPS 2023 - [c85]Paul Pu Liang, Zihao Deng, Martin Q. Ma, James Y. Zou, Louis-Philippe Morency, Ruslan Salakhutdinov:
Factorized Contrastive Learning: Going Beyond Multi-view Redundancy. NeurIPS 2023 - [c84]Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W. Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi:
DataPerf: Benchmarks for Data-Centric AI Development. NeurIPS 2023 - [c83]Mert Yüksekgönül, Linjun Zhang, James Y. Zou, Carlos Guestrin:
Beyond Confidence: Reliable Models Should Also Consider Atypicality. NeurIPS 2023 - [i133]Roxana Daneshjou, Mert Yüksekgönül, Zhuo Ran Cai, Roberto A. Novoa, James Zou:
SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained model debugging and analysis. CoRR abs/2302.00785 (2023) - [i132]Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung:
Diagnosing and Rectifying Vision Models using Language. CoRR abs/2302.04269 (2023) - [i131]Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang:
Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. CoRR abs/2302.06232 (2023) - [i130]Weixin Liang, Mert Yüksekgönül, Yining Mao, Eric Wu, James Zou:
GPT detectors are biased against non-native English writers. CoRR abs/2304.02819 (2023) - [i129]Yuzhen Mao, Zhun Deng, Huaxiu Yao, Ting Ye, Kenji Kawaguchi, James Zou:
Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks. CoRR abs/2304.03935 (2023) - [i128]Yongchan Kwon, James Zou:
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value. CoRR abs/2304.07718 (2023) - [i127]Zachary Izzo, Ruishan Liu, James Zou:
Data-Driven Subgroup Identification for Linear Regression. CoRR abs/2305.00195 (2023) - [i126]Shirley Wu, Mert Yüksekgönül, Linjun Zhang, James Zou:
Discover and Cure: Concept-aware Mitigation of Spurious Correlation. CoRR abs/2305.00650 (2023) - [i125]Weixin Liang, Yining Mao, Yongchan Kwon, Xinyu Yang, James Zou:
Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations. CoRR abs/2305.02995 (2023) - [i124]Lingjiao Chen, Matei Zaharia, James Zou:
FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance. CoRR abs/2305.05176 (2023) - [i123]Yuhui Zhang, Michihiro Yasunaga, Zhengping Zhou, Jeff Z. HaoChen, James Zou, Percy Liang, Serena Yeung:
Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models. CoRR abs/2305.17311 (2023) - [i122]Mert Yüksekgönül, Linjun Zhang, James Zou, Carlos Guestrin:
Beyond Confidence: Reliable Models Should Also Consider Atypicality. CoRR abs/2305.18262 (2023) - [i121]Paul Pu Liang, Zihao Deng, Martin Q. Ma, James Zou, Louis-Philippe Morency, Ruslan Salakhutdinov:
Factorized Contrastive Learning: Going Beyond Multi-view Redundancy. CoRR abs/2306.05268 (2023) - [i120]Kailas Vodrahalli, James Zou:
ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations. CoRR abs/2306.08141 (2023) - [i119]Yiqun T. Chen, James Zou:
TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter. CoRR abs/2306.08310 (2023) - [i118]Kevin Fu Jiang, Weixin Liang, James Zou, Yongchan Kwon:
OpenDataVal: a Unified Benchmark for Data Valuation. CoRR abs/2306.10577 (2023) - [i117]Xinming Tu, James Zou, Weijie J. Su, Linjun Zhang:
What Should Data Science Education Do with Large Language Models? CoRR abs/2307.02792 (2023) - [i116]Lingjiao Chen, Matei Zaharia, James Zou:
How is ChatGPT's behavior changing over time? CoRR abs/2307.09009 (2023) - [i115]Rong Ma, Eric D. Sun, David Donoho, James Zou:
Is your data alignable? Principled and interpretable alignability testing and integration of single-cell data. CoRR abs/2308.01839 (2023) - [i114]Jesutofunmi A. Omiye, Haiwen Gui, Shawheen J. Rezaei, James Zou, Roxana Daneshjou:
Large language models in medicine: the potentials and pitfalls. CoRR abs/2309.00087 (2023) - [i113]Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, James Zou:
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions. CoRR abs/2309.07875 (2023) - [i112]Yongchan Kwon, Eric Wu, Kevin Wu, James Zou:
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models. CoRR abs/2310.00902 (2023) - [i111]Weixin Liang, Yuhui Zhang, Hancheng Cao, Binglu Wang, Daisy Ding, Xinyu Yang, Kailas Vodrahalli, Siyu He, Daniel Scott Smith, Yian Yin, Daniel A. McFarland, James Zou:
Can large language models provide useful feedback on research papers? A large-scale empirical analysis. CoRR abs/2310.01783 (2023) - [i110]Chenhang Cui, Yiyang Zhou, Xinyu Yang, Shirley Wu, Linjun Zhang, James Zou, Huaxiu Yao:
Holistic Analysis of Hallucination in GPT-4V(ision): Bias and Interference Challenges. CoRR abs/2311.03287 (2023) - [i109]Sheng Liu, Lei Xing, James Zou:
In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering. CoRR abs/2311.06668 (2023) - [i108]Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed M. Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt D. Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson:
DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR abs/2311.13028 (2023) - [i107]Lingjiao Chen, Bilge Acun, Newsha Ardalani, Yifan Sun, Feiyang Kang, Hanrui Lyu, Yongchan Kwon, Ruoxi Jia, Carole-Jean Wu, Matei Zaharia, James Zou:
Data Acquisition: A New Frontier in Data-centric AI. CoRR abs/2311.13712 (2023) - [i106]Angela Zhang, Mert Yüksekgönül, Joshua Guild, James Zou, Joseph C. Wu:
ChatGPT Exhibits Gender and Racial Biases in Acute Coronary Syndrome Management. CoRR abs/2311.14703 (2023) - [i105]Shirley Wu, Kaidi Cao, Bruno Ribeiro, James Zou, Jure Leskovec:
GraphMETRO: Mitigating Complex Distribution Shifts in GNNs via Mixture of Aligned Experts. CoRR abs/2312.04693 (2023) - [i104]Simran Arora, Sabri Eyuboglu, Aman Timalsina, Isys Johnson, Michael Poli, James Zou, Atri Rudra, Christopher Ré:
Zoology: Measuring and Improving Recall in Efficient Language Models. CoRR abs/2312.04927 (2023) - [i103]Jiachen Zhao, Zhun Deng, David Madras, James Zou, Mengye Ren:
Learning and Forgetting Unsafe Examples in Large Language Models. CoRR abs/2312.12736 (2023) - 2022
- [j20]Amirata Ghorbani, Dina Berenbaum, Maor Ivgi, Yuval Dafna, James Y. Zou:
Beyond Importance Scores: Interpreting Tabular ML by Visualizing Feature Semantics. Inf. 13(1): 15 (2022) - [j19]Cameron Buckner, Risto Miikkulainen, Stephanie Forrest, Silvia Milano, James Zou, Carina Prunk, Christopher Irrgang, I. Glenn Cohen, Hao Su, Robin R. Murphy, Russell H. Taylor, Axel Krieger, Mirko Kovac, Jathan Sadowski, Vidushi Marda:
AI reflections in 2021. Nat. Mach. Intell. 4(1): 5-10 (2022) - [j18]Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou:
Advances, challenges and opportunities in creating data for trustworthy AI. Nat. Mach. Intell. 4(8): 669-677 (2022) - [j17]Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou:
Author Correction: Advances, challenges and opportunities in creating data for trustworthy AI. Nat. Mac. Intell. 4(10): 904 (2022) - [j16]Andre Esteva, Jean Feng, Douwe van der Wal, Shih-Cheng Huang, Jeffry P. Simko, Sandy Devries, Emmalyn Chen, Edward M. Schaeffer, Todd M. Morgan, Yilun Sun, Amirata Ghorbani, Nikhil Naik, Dhruv Nathawani, Richard Socher, Jeff M. Michalski, Mack Roach, Thomas M. Pisansky, Jedidiah M. Monson, Farah Naz, James Wallace, Michelle J. Ferguson, Jean-Paul Bahary, James Zou, Matthew P. Lungren, Serena Yeung, Ashley E. Ross, Michael J. Kucharczyk, Luis Souhami, Leslie Ballas, Christopher A. Peters, Sandy Liu, Alexander G. Balogh, Pamela D. Randolph-Jackson, David L. Schwartz, Michael R. Girvigian, Naoyuki G. Saito, Adam Raben, Rachel A. Rabinovitch, Khalil Katato, Howard M. Sandler, Phuoc T. Tran, Daniel E. Spratt, Stephanie Pugh, Felix Y. Feng, Osama Mohamad:
Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials. npj Digit. Medicine 5 (2022) - [j15]Weixin Liang, Scott Elrod, Daniel A. McFarland, James Zou:
Systematic analysis of 50 years of Stanford University technology transfer and commercialization. Patterns 3(9): 100584 (2022) - [j14]Yongchan Kwon, Tony Ginart, James Zou:
Competition over data: how does data purchase affect users? Trans. Mach. Learn. Res. 2022 (2022) - [c82]Ruishan Liu, James Zou:
Data Sculpting: Interpretable Algorithm for End-to-End Cohort Selection. IEEECONF 2022: 263-270 - [c81]Amirata Ghorbani, Andre Esteva, James Zou:
Grading of Prostate Whole-slide Images Using Weak Self-supervised Learning. IEEECONF 2022: 1439-1443 - [c80]Amirata Ghorbani, James Zou, Andre Esteva:
Data Shapley Valuation for Efficient Batch Active Learning. IEEECONF 2022: 1456-1462 - [c79]Kailas Vodrahalli, Roxana Daneshjou, Tobias Gerstenberg, James Zou:
Do Humans Trust Advice More if it Comes from AI?: An Analysis of Human-AI Interactions. AIES 2022: 763-777 - [c78]Tony Ginart, Martin Jinye Zhang, James Zou:
MLDemon: Deployment Monitoring for Machine Learning Systems. AISTATS 2022: 3962-3997 - [c77]Zachary Izzo, James Zou, Lexing Ying:
How to Learn when Data Gradually Reacts to Your Model. AISTATS 2022: 3998-4035 - [c76]Yongchan Kwon, James Zou:
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning. AISTATS 2022: 8780-8802 - [c75]Tarek Naous, Srinjay Sarkar, Abubakar Abid, James Zou:
Clustering Plotted Data by Image Segmentation. CVPR 2022: 21467-21472 - [c74]Sabri Eyuboglu, Bojan Karlas, Christopher Ré, Ce Zhang, James Zou:
dcbench: a benchmark for data-centric AI systems. DEEM@SIGMOD 2022: 9:1-9:4 - [c73]Nazneen Rajani, Weixin Liang, Lingjiao Chen, Margaret Mitchell, James Zou:
SEAL: Interactive Tool for Systematic Error Analysis and Labeling. EMNLP (Demos) 2022: 359-370 - [c72]Lingjiao Chen, Matei Zaharia, James Zou:
How Did the Model Change? Efficiently Assessing Machine Learning API Shifts. ICLR 2022 - [c71]Sabri Eyuboglu, Maya Varma, Khaled Kamal Saab, Jean-Benoit Delbrouck, Christopher Lee-Messer, Jared Dunnmon, James Zou, Christopher Ré:
Domino: Discovering Systematic Errors with Cross-Modal Embeddings. ICLR 2022 - [c70]Weixin Liang, James Zou:
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts. ICLR 2022 - [c69]Abubakar Abid, Mert Yüksekgönül, James Zou:
Meaningfully debugging model mistakes using conceptual counterfactual explanations. ICML 2022: 66-88 - [c68]Lingjiao Chen, Matei Zaharia, James Zou:
Efficient Online ML API Selection for Multi-Label Classification Tasks. ICML 2022: 3716-3746 - [c67]Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn:
Improving Out-of-Distribution Robustness via Selective Augmentation. ICML 2022: 25407-25437 - [c66]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou:
When and How Mixup Improves Calibration. ICML 2022: 26135-26160 - [c65]Prashnna K. Gyawali, Xiaoxia Liu, James Zou, Zihuai He:
Ensembling improves stability and power of feature selection for deep learning models. MLCB 2022: 33-45 - [c64]Kyle Swanson, Howard Chang, James Zou:
Predicting Immune Escape with Pretrained Protein Language Model Embeddings. MLCB 2022: 110-130 - [c63]Lingjiao Chen, Zhihua Jin, Sabri Eyuboglu, Christopher Ré, Matei Zaharia, James Y. Zou:
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions. NeurIPS 2022 - [c62]Lingjiao Chen, Matei Zaharia, James Y. Zou:
Estimating and Explaining Model Performance When Both Covariates and Labels Shift. NeurIPS 2022 - [c61]Roxana Daneshjou, Mert Yüksekgönül, Zhuo Ran Cai, Roberto A. Novoa, James Y. Zou:
SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained debugging and analysis. NeurIPS 2022 - [c60]Yongchan Kwon, James Y. Zou:
WeightedSHAP: analyzing and improving Shapley based feature attributions. NeurIPS 2022 - [c59]Weixin Liang, Yuhui Zhang, Yongchan Kwon, Serena Yeung, James Y. Zou:
Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning. NeurIPS 2022 - [c58]Kailas Vodrahalli, Tobias Gerstenberg, James Y. Zou:
Uncalibrated Models Can Improve Human-AI Collaboration. NeurIPS 2022 - [c57]Huaxiu Yao, Yiping Wang, Linjun Zhang, James Y. Zou, Chelsea Finn:
C-Mixup: Improving Generalization in Regression. NeurIPS 2022 - [i102]Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn:
Improving Out-of-Distribution Robustness via Selective Augmentation. CoRR abs/2201.00299 (2022) - [i101]Antonio Ginart, Laurens van der Maaten, James Zou, Chuan Guo:
Submix: Practical Private Prediction for Large-Scale Language Models. CoRR abs/2201.00971 (2022) - [i100]Yongchan Kwon, Antonio Ginart, James Zou:
Competition over data: how does data purchase affect users? CoRR abs/2201.10774 (2022) - [i99]Kailas Vodrahalli, Tobias Gerstenberg, James Zou:
Uncalibrated Models Can Improve Human-AI Collaboration. CoRR abs/2202.05983 (2022) - [i98]Weixin Liang, James Zou:
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts. CoRR abs/2202.06523 (2022) - [i97]Weixin Liang, Yuhui Zhang, Yongchan Kwon, Serena Yeung, James Zou:
Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning. CoRR abs/2203.02053 (2022) - [i96]Roxana Daneshjou, Kailas Vodrahalli, Roberto A. Novoa, Melissa Jenkins, Weixin Liang, Veronica Rotemberg, Justin Ko, Susan M. Swetter, Elizabeth E. Bailey, Olivier Gevaert, Pritam Mukherjee, Michelle Phung, Kiana Yekrang, Bradley Fong, Rachna Sahasrabudhe, Johan A. C. Allerup, Utako Okata-Karigane, James Zou, Albert Chiou:
Disparities in Dermatology AI Performance on a Diverse, Curated Clinical Image Set. CoRR abs/2203.08807 (2022) - [i95]Sabri Eyuboglu, Maya Varma, Khaled Saab, Jean-Benoit Delbrouck, Christopher Lee-Messer, Jared Dunnmon, James Zou, Christopher Ré:
Domino: Discovering Systematic Errors with Cross-Modal Embeddings. CoRR abs/2203.14960 (2022) - [i94]David Ouyang, John Theurer, Nathan R. Stein, J. Weston Hughes, Pierre A. Elias, Bryan He, Neal Yuan, Grant Duffy, Roopinder K. Sandhu, Joseph Ebinger, Patrick Botting, Melvin Jujjavarapu, Brian Claggett, James E. Tooley, Tim Poterucha, Jonathan H. Chen, Michael Nurok, Marco V. Perez, Adler J. Perotte, James Y. Zou, Nancy R. Cook, Sumeet S. Chugh, Susan Cheng, Christine M. Albert:
Electrocardiographic Deep Learning for Predicting Post-Procedural Mortality. CoRR abs/2205.03242 (2022) - [i93]Prashnna K. Gyawali, Yann Le Guen, Xiaoxia Liu, Hua Tang, James Zou, Zihuai He:
Improving genetic risk prediction across diverse population by disentangling ancestry representations. CoRR abs/2205.04673 (2022) - [i92]Jaime Roquero Gimenez, James Y. Zou:
A Unified f-divergence Framework Generalizing VAE and GAN. CoRR abs/2205.05214 (2022) - [i91]Mert Yüksekgönül, Maggie Wang, James Zou:
Post-hoc Concept Bottleneck Models. CoRR abs/2205.15480 (2022) - [i90]Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou:
FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. CoRR abs/2206.02792 (2022) - [i89]Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew M. Dai, Andrew La, Andrew K. Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakas, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartlomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, Cèsar Ferri Ramírez, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Chris Waites, Christian Voigt, Christopher D. Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodolà, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A. Chi, Ethan Dyer, Ethan J. Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, François Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Wang, Gonzalo Jaimovitch-López, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Shevlin, Hinrich Schütze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B. Simon, James Koppel, James Zheng, James Zou, Jan Kocon, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse H. Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, José Hernández-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh D. Dhole, Kevin Gimpel, Kevin Omondi, Kory W. Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros Colón, Luke Metz, Lütfi Kerem Senel, Maarten Bosma, Maarten Sap, Maartje ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, María José Ramírez-Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L. Leavitt, Matthias Hagen, Mátyás Schubert, Medina Baitemirova, Melody Arnaud, Melvin McElrath, Michael A. Yee, Michael Cohen, Michael Gu, Michael I. Ivanitskiy, Michael Starritt, Michael Strube, Michal Swedrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T., Nanyun Peng, Nathan A. Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Milkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan LeBras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Ruslan Salakhutdinov, Ryan Chi, Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel S. Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima (Shammie) Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven T. Piantadosi, Stuart M. Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsu Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay V. Ramasesh, Vinay Uday Prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, Zirui Wang, Ziyi Wu:
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. CoRR abs/2206.04615 (2022) - [i88]Zhiying Zhu, Weixin Liang, James Zou:
GSCLIP : A Framework for Explaining Distribution Shifts in Natural Language. CoRR abs/2206.15007 (2022) - [i87]Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Juan Ciro, Lora Aroyo, Bilge Acun, Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Tariq Kane, Christine R. Kirkpatrick, Tzu-Sheng Kuo, Jonas Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi:
DataPerf: Benchmarks for Data-Centric AI Development. CoRR abs/2207.10062 (2022) - [i86]Lingjiao Chen, Matei Zaharia, James Zou:
Estimating and Explaining Model Performance When Both Covariates and Labels Shift. CoRR abs/2209.08436 (2022) - [i85]Lingjiao Chen, Zhihua Jin, Sabri Eyuboglu, Christopher Ré, Matei Zaharia, James Zou:
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions. CoRR abs/2209.08443 (2022) - [i84]Kailas Vodrahalli, Justin Ko, Albert S. Chiou, Roberto A. Novoa, Abubakar Abid, Michelle Phung, Kiana Yekrang, Paige Petrone, James Zou, Roxana Daneshjou:
Development and Clinical Evaluation of an AI Support Tool for Improving Telemedicine Photo Quality. CoRR abs/2209.09105 (2022) - [i83]Yongchan Kwon, James Zou:
WeightedSHAP: analyzing and improving Shapley based feature attributions. CoRR abs/2209.13429 (2022) - [i82]Kevin E. Wu, Kevin K. Yang, Rianne van den Berg, James Y. Zou, Alex X. Lu, Ava P. Amini:
Protein structure generation via folding diffusion. CoRR abs/2209.15611 (2022) - [i81]Prashnna K. Gyawali, Xiaoxia Liu, James Zou, Zihuai He:
Ensembling improves stability and power of feature selection for deep learning models. CoRR abs/2210.00604 (2022) - [i80]Xinyi Zhao, Weixin Liang, James Zou:
Data Budgeting for Machine Learning. CoRR abs/2210.00987 (2022) - [i79]Mert Yüksekgönül, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, James Zou:
When and why vision-language models behave like bags-of-words, and what to do about it? CoRR abs/2210.01936 (2022) - [i78]Zhenbang Wu, Huaxiu Yao, Zhe Su, David M. Liebovitz, Lucas M. Glass, James Zou, Chelsea Finn, Jimeng Sun:
Knowledge-Driven New Drug Recommendation. CoRR abs/2210.05572 (2022) - [i77]Huaxiu Yao, Yiping Wang, Linjun Zhang, James Zou, Chelsea Finn:
C-Mixup: Improving Generalization in Regression. CoRR abs/2210.05775 (2022) - [i76]Nazneen Rajani, Weixin Liang, Lingjiao Chen, Meg Mitchell, James Zou:
SEAL : Interactive Tool for Systematic Error Analysis and Labeling. CoRR abs/2210.05839 (2022) - [i75]Haotian Ye, James Zou, Linjun Zhang:
Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise. CoRR abs/2210.11075 (2022) - [i74]Rong Ma, Eric D. Sun, James Zou:
A Spectral Method for Assessing and Combining Multiple Data Visualizations. CoRR abs/2210.13711 (2022) - [i73]Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, Aylin Caliskan:
Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale. CoRR abs/2211.03759 (2022) - [i72]Zachary Izzo, Jinsung Yoon, Sercan Ö. Arik, James Zou:
Provable Membership Inference Privacy. CoRR abs/2211.06582 (2022) - [i71]Puheng Li, James Zou, Linjun Zhang:
FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee. CoRR abs/2211.15072 (2022) - 2021
- [j13]Dylan Haynes, Anusri Pampari, Christina Topham, Kathryn Schwarzenberger, Michael Heath, James Zou, Teri M. Greiling:
Patient Experience Surveys Reveal Gender-Biased Descriptions of Their Care Providers. J. Medical Syst. 45(10): 90 (2021) - [j12]Abubakar Abid, Maheen Farooqi, James Zou:
Large language models associate Muslims with violence. Nat. Mach. Intell. 3(6): 461-463 (2021) - [c56]Abubakar Abid, Maheen Farooqi, James Zou:
Persistent Anti-Muslim Bias in Large Language Models. AIES 2021: 298-306 - [c55]Gal Yona, Amirata Ghorbani, James Zou:
Who's Responsible? Jointly Quantifying the Contribution of the Learning Algorithm and Data. AIES 2021: 1034-1041 - [c54]Yongchan Kwon, Manuel A. Rivas, James Zou:
Efficient Computation and Analysis of Distributional Shapley Values. AISTATS 2021: 793-801 - [c53]Tony Ginart, Eva Zhang, Yongchan Kwon, James Zou:
Competing AI: How does competition feedback affect machine learning? AISTATS 2021: 1693-1701 - [c52]Zachary Izzo, Mary Anne Smart, Kamalika Chaudhuri, James Zou:
Approximate Data Deletion from Machine Learning Models. AISTATS 2021: 2008-2016 - [c51]Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou:
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. AISTATS 2021: 2845-2853 - [c50]Girmaw Abebe Tadesse, Celia Cintas, Roxana Daneshjou, Kush R. Varshney, Peter W. J. Staar, Skyler Speakman, Kenya Andrews, Chinyere Agunwa, Justin Jia, Elizabeth E. Bailey, Jules Lipoff, Ginikanwa Onyekaba, Veronica Rotemberg, Ademide Adelekun, James Y. Zou:
Racial Representation Analysis in Dermatology Academic Materials. AMIA 2021 - [c49]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou:
How Does Mixup Help With Robustness and Generalization? ICLR 2021 - [c48]Zachary Izzo, Lexing Ying, James Zou:
How to Learn when Data Reacts to Your Model: Performative Gradient Descent. ICML 2021: 4641-4650 - [c47]Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui Li:
Improving Generalization in Meta-learning via Task Augmentation. ICML 2021: 11887-11897 - [c46]Weixin Liang, James Zou:
Neural Group Testing to Accelerate Deep Learning. ISIT 2021: 958-963 - [c45]Antonio A. Ginart, Maxim Naumov, Dheevatsa Mudigere, Jiyan Yang, James Zou:
Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems. ISIT 2021: 2786-2791 - [c44]Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Y. Zou:
Adversarial Training Helps Transfer Learning via Better Representations. NeurIPS 2021: 25179-25191 - [c43]Kailas Vodrahalli, Roxana Daneshjou, Roberto A. Novoa, Albert Chiou, Justin M. Ko, James Zou:
TrueImage: A Machine Learning Algorithm to Improve the Quality of Telehealth Photos. PSB 2021 - [i70]Abubakar Abid, Maheen Farooqi, James Zou:
Persistent Anti-Muslim Bias in Large Language Models. CoRR abs/2101.05783 (2021) - [i69]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou:
When and How Mixup Improves Calibration. CoRR abs/2102.06289 (2021) - [i68]Zachary Izzo, Lexing Ying, James Zou:
How to Learn when Data Reacts to Your Model: Performative Gradient Descent. CoRR abs/2102.07698 (2021) - [i67]Lingjiao Chen, Matei Zaharia, James Zou:
FrugalMCT: Efficient Online ML API Selection for Multi-Label Classification Tasks. CoRR abs/2102.09127 (2021) - [i66]Amirata Ghorbani, James Zou, Andre Esteva:
Data Shapley Valuation for Efficient Batch Active Learning. CoRR abs/2104.08312 (2021) - [i65]Antonio Ginart, Martin Jinye Zhang, James Zou:
MLDemon: Deployment Monitoring for Machine Learning Systems. CoRR abs/2104.13621 (2021) - [i64]Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Zou:
Adversarial Training Helps Transfer Learning via Better Representations. CoRR abs/2106.10189 (2021) - [i63]Farzan Farnia, Amirali Aghazadeh, James Zou, David Tse:
Group-Structured Adversarial Training. CoRR abs/2106.10324 (2021) - [i62]Grant Duffy, Paul P. Cheng, Neal Yuan, Bryan He, Alan C. Kwan, Matthew J. Shun-Shin, Kevin M. Alexander, Joseph Ebinger, Matthew P. Lungren, Florian Rader, David H. Liang, Ingela Schnittger, Euan A. Ashley, James Y. Zou, Jignesh Patel, Ronald Witteles, Susan Cheng, David Ouyang:
High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy with Cardiovascular Deep Learning. CoRR abs/2106.12511 (2021) - [i61]Abubakar Abid, James Zou:
Meaningfully Explaining a Model's Mistakes. CoRR abs/2106.12723 (2021) - [i60]Kailas Vodrahalli, Tobias Gerstenberg, James Zou:
Do Humans Trust Advice More if it Comes from AI? An Analysis of Human-AI Interactions. CoRR abs/2107.07015 (2021) - [i59]Lingjiao Chen, Tracy Cai, Matei Zaharia, James Zou:
Did the Model Change? Efficiently Assessing Machine Learning API Shifts. CoRR abs/2107.14203 (2021) - [i58]Wenlong Ji, Zhun Deng, Ryumei Nakada, James Zou, Linjun Zhang:
The Power of Contrast for Feature Learning: A Theoretical Analysis. CoRR abs/2110.02473 (2021) - [i57]Tarek Naous, Srinjay Sarkar, Abubakar Abid, James Zou:
Clustering Plotted Data by Image Segmentation. CoRR abs/2110.05187 (2021) - [i56]Yongchan Kwon, James Zou:
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning. CoRR abs/2110.14049 (2021) - [i55]Amirata Ghorbani, Dina Berenbaum, Maor Ivgi, Yuval Dafna, James Zou:
Beyond Importance Scores: Interpreting Tabular ML by Visualizing Feature Semantics. CoRR abs/2111.05898 (2021) - [i54]Roxana Daneshjou, Kailas Vodrahalli, Weixin Liang, Roberto A. Novoa, Melissa Jenkins, Veronica Rotemberg, Justin Ko, Susan M. Swetter, Elizabeth E. Bailey, Olivier Gevaert, Pritam Mukherjee, Michelle Phung, Kiana Yekrang, Bradley Fong, Rachna Sahasrabudhe, James Zou, Albert Chiou:
Disparities in Dermatology AI: Assessments Using Diverse Clinical Images. CoRR abs/2111.08006 (2021) - [i53]Eric Wu, Kevin Wu, James Zou:
Explaining medical AI performance disparities across sites with confounder Shapley value analysis. CoRR abs/2111.08168 (2021) - [i52]Zachary Izzo, James Zou, Lexing Ying:
How to Learn when Data Gradually Reacts to Your Model. CoRR abs/2112.07042 (2021) - 2020
- [j11]Zhenqin Wu, Nilah M. Ioannidis, James Zou, Russell Schwartz:
Predicting target genes of non-coding regulatory variants with IRT. Bioinform. 36(16): 4440-4448 (2020) - [j10]Abubakar Abid, Ali Abdalla, Ali Abid, Dawood Khan, Abdulrahman Alfozan, James Zou:
An online platform for interactive feedback in biomedical machine learning. Nat. Mach. Intell. 2(2): 86-88 (2020) - [j9]David Ouyang, Bryan He, Amirata Ghorbani, Neal Yuan, Joseph Ebinger, Curtis P. Langlotz, Paul A. Heidenreich, Robert A. Harrington, David H. Liang, Euan A. Ashley, James Y. Zou:
Video-based AI for beat-to-beat assessment of cardiac function. Nat. 580(7802): 252-256 (2020) - [j8]Amirata Ghorbani, David Ouyang, Abubakar Abid, Bryan He, Jonathan H. Chen, Robert A. Harrington, David H. Liang, Euan A. Ashley, James Y. Zou:
Deep learning interpretation of echocardiograms. npj Digit. Medicine 3 (2020) - [j7]Daniel Russo, James Zou:
How Much Does Your Data Exploration Overfit? Controlling Bias via Information Usage. IEEE Trans. Inf. Theory 66(1): 302-323 (2020) - [c42]Weixin Liang, James Zou, Zhou Yu:
Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation. ACL 2020: 1363-1374 - [c41]Weixin Liang, James Zou, Zhou Yu:
ALICE: Active Learning with Contrastive Natural Language Explanations. EMNLP (1) 2020: 4380-4391 - [c40]Ruishan Liu, Akshay Balsubramani, James Zou:
Learning transport cost from subset correspondence. ICLR 2020 - [c39]Amirata Ghorbani, Michael P. Kim, James Zou:
A Distributional Framework For Data Valuation. ICML 2020: 3535-3544 - [c38]Lingjiao Chen, Matei Zaharia, James Y. Zou:
FrugalML: How to use ML Prediction APIs more accurately and cheaply. NeurIPS 2020 - [c37]Amirata Ghorbani, James Y. Zou:
Neuron Shapley: Discovering the Responsible Neurons. NeurIPS 2020 - [c36]Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Y. Zou, Sergey Levine, Chelsea Finn, Tengyu Ma:
MOPO: Model-based Offline Policy Optimization. NeurIPS 2020 - [c35]Allen Nie, Arturo L. Pineda, Matt W. Wright, Hannah Wand, Bryan Wulf, Helio A. Costa, Ronak Y. Patel, Carlos D. Bustamante, James Zou:
LitGen: Genetic Literature Recommendation Guided by Human Explanations. PSB 2020: 67-78 - [i51]Amirata Ghorbani, James Y. Zou:
Neuron Shapley: Discovering the Responsible Neurons. CoRR abs/2002.09815 (2020) - [i50]Zachary Izzo, Mary Anne Smart, Kamalika Chaudhuri, James Y. Zou:
Approximate Data Deletion from Machine Learning Models: Algorithms and Evaluations. CoRR abs/2002.10077 (2020) - [i49]Amirata Ghorbani, Michael P. Kim, James Y. Zou:
A Distributional Framework for Data Valuation. CoRR abs/2002.12334 (2020) - [i48]Abubakar Abid, James Y. Zou:
Improving Training on Noisy Stuctured Labels. CoRR abs/2003.03862 (2020) - [i47]Weixin Liang, James Zou, Zhou Yu:
Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation. CoRR abs/2005.10716 (2020) - [i46]Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, Tengyu Ma:
MOPO: Model-based Offline Policy Optimization. CoRR abs/2005.13239 (2020) - [i45]Lingjiao Chen, Matei Zaharia, James Zou:
FrugalML: How to Use ML Prediction APIs More Accurately and Cheaply. CoRR abs/2006.07512 (2020) - [i44]Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Y. Zou:
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. CoRR abs/2006.08476 (2020) - [i43]Yongchan Kwon, Manuel A. Rivas, James Zou:
Efficient computation and analysis of distributional Shapley values. CoRR abs/2007.01357 (2020) - [i42]Antonio Ginart, Eva Zhang, James Zou:
Competing AI: How competition feedback affects machine learning. CoRR abs/2009.06797 (2020) - [i41]Weixin Liang, James Zou, Zhou Yu:
ALICE: Active Learning with Contrastive Natural Language Explanations. CoRR abs/2009.10259 (2020) - [i40]Kailas Vodrahalli, Roxana Daneshjou, Roberto A. Novoa, Albert Chiou, Justin M. Ko, James Zou:
TrueImage: A Machine Learning Algorithm to Improve the Quality of Telehealth Photos. CoRR abs/2010.02086 (2020) - [i39]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Y. Zou:
How Does Mixup Help With Robustness and Generalization? CoRR abs/2010.04819 (2020) - [i38]Siyi Tang, Amirata Ghorbani, Rikiya Yamashita, Sameer Rehman, Jared A. Dunnmon, James Y. Zou, Daniel L. Rubin:
Data Valuation for Medical Imaging Using Shapley Value: Application on A Large-scale Chest X-ray Dataset. CoRR abs/2010.08006 (2020) - [i37]Weixin Liang, James Zou:
Neural Group Testing to Accelerate Deep Learning. CoRR abs/2011.10704 (2020)
2010 – 2019
- 2019
- [j6]Anvita Gupta, James Zou:
Feedback GAN for DNA optimizes protein functions. Nat. Mach. Intell. 1(2): 105-111 (2019) - [j5]Cara Tannenbaum, Robert P. Ellis, Friederike Eyssel, James Zou, Londa Schiebinger:
Sex and gender analysis improves science and engineering. Nat. 575(7781): 137-146 (2019) - [j4]Yuhui Zhang, Allen Nie, Ashley Zehnder, Rodney López Page, James Zou:
VetTag: improving automated veterinary diagnosis coding via large-scale language modeling. npj Digit. Medicine 2 (2019) - [c34]Amirata Ghorbani, Abubakar Abid, James Y. Zou:
Interpretation of Neural Networks Is Fragile. AAAI 2019: 3681-3688 - [c33]Michael P. Kim, Amirata Ghorbani, James Y. Zou:
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification. AIES 2019: 247-254 - [c32]Jaime Roquero Gimenez, Amirata Ghorbani, James Y. Zou:
Knockoffs for the Mass: New Feature Importance Statistics with False Discovery Guarantees. AISTATS 2019: 2125-2133 - [c31]Jaime Roquero Gimenez, James Y. Zou:
Improving the Stability of the Knockoff Procedure: Multiple Simultaneous Knockoffs and Entropy Maximization. AISTATS 2019: 2184-2192 - [c30]Abdi-Hakin Dirie, Abubakar Abid, James Y. Zou:
Contrastive Multivariate Singular Spectrum Analysis. Allerton 2019: 1122-1127 - [c29]Hongyao Ma, Reshef Meir, David C. Parkes, James Y. Zou:
Contingent Payment Mechanisms for Resource Utilization. AAMAS 2019: 422-430 - [c28]Muhammed Fatih Balin, Abubakar Abid, James Y. Zou:
Concrete Autoencoders: Differentiable Feature Selection and Reconstruction. ICML 2019: 444-453 - [c27]Amirata Ghorbani, James Y. Zou:
Data Shapley: Equitable Valuation of Data for Machine Learning. ICML 2019: 2242-2251 - [c26]Jaime Roquero Gimenez, James Y. Zou:
Discovering Conditionally Salient Features with Statistical Guarantees. ICML 2019: 2290-2298 - [c25]Martin J. Zhang, James Zou, David Tse:
Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits. ICML 2019: 7512-7522 - [c24]Dorottya Demszky, Nikhil Garg, Rob Voigt, James Zou, Jesse Shapiro, Matthew Gentzkow, Dan Jurafsky:
Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootings. NAACL-HLT (1) 2019: 2970-3005 - [c23]Antonio Ginart, Melody Y. Guan, Gregory Valiant, James Zou:
Making AI Forget You: Data Deletion in Machine Learning. NeurIPS 2019: 3513-3526 - [c22]Amirata Ghorbani, James Wexler, James Y. Zou, Been Kim:
Towards Automatic Concept-based Explanations. NeurIPS 2019: 9273-9282 - [c21]Martin J. Zhang, Fei Xia, James Zou:
AdaFDR: A Fast, Powerful and Covariate-Adaptive Approach to Multiple Hypothesis Testing. RECOMB 2019: 330-333 - [i36]Abubakar Abid, Muhammad Fatih Balin, James Y. Zou:
Concrete Autoencoders for Differentiable Feature Selection and Reconstruction. CoRR abs/1901.09346 (2019) - [i35]Martin J. Zhang, James Zou, David Tse:
Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits. CoRR abs/1902.00197 (2019) - [i34]Abubakar Abid, James Y. Zou:
Contrastive Variational Autoencoder Enhances Salient Features. CoRR abs/1902.04601 (2019) - [i33]Dorottya Demszky, Nikhil Garg, Rob Voigt, James Zou, Matthew Gentzkow, Jesse Shapiro, Dan Jurafsky:
Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootings. CoRR abs/1904.01596 (2019) - [i32]Amirata Ghorbani, James Y. Zou:
Data Shapley: Equitable Valuation of Data for Machine Learning. CoRR abs/1904.02868 (2019) - [i31]Jaime Roquero Gimenez, James Y. Zou:
Discovering Conditionally Salient Features with Statistical Guarantees. CoRR abs/1905.12177 (2019) - [i30]Abubakar Abid, Ali Abdalla, Ali Abid, Dawood Khan, Abdulrahman Alfozan, James Y. Zou:
Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild. CoRR abs/1906.02569 (2019) - [i29]Antonio Ginart, Melody Y. Guan, Gregory Valiant, James Zou:
Making AI Forget You: Data Deletion in Machine Learning. CoRR abs/1907.05012 (2019) - [i28]Allen Nie, Arturo L. Pineda, Matt W. Wright, Hannah Wand, Bryan Wulf, Helio A. Costa, Ronak Y. Patel, Carlos D. Bustamante, James Zou:
LitGen: Genetic Literature Recommendation Guided by Human Explanations. CoRR abs/1909.10699 (2019) - [i27]Antonio Ginart, Maxim Naumov, Dheevatsa Mudigere, Jiyan Yang, James Zou:
Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems. CoRR abs/1909.11810 (2019) - [i26]Ruishan Liu, Akshay Balsubramani, James Zou:
Learning transport cost from subset correspondence. CoRR abs/1909.13203 (2019) - [i25]Gal Yona, Amirata Ghorbani, James Y. Zou:
Who's responsible? Jointly quantifying the contribution of the learning algorithm and training data. CoRR abs/1910.04214 (2019) - 2018
- [j3]Allen Nie, Ashley Zehnder, Rodney López Page, Yuhui Zhang, Arturo López Pineda, Manuel A. Rivas, Carlos D. Bustamante, James Zou:
DeepTag: inferring diagnoses from veterinary clinical notes. npj Digit. Medicine 1 (2018) - [j2]Nikhil Garg, Londa Schiebinger, Dan Jurafsky, James Zou:
Word embeddings quantify 100 years of gender and ethnic stereotypes. Proc. Natl. Acad. Sci. USA 115(16): E3635-E3644 (2018) - [c20]Xinkun Nie, Xiaoying Tian, Jonathan Taylor, James Zou:
Why Adaptively Collected Data Have Negative Bias and How to Correct for It. AISTATS 2018: 1261-1269 - [c19]Amirata Ghorbani, James Y. Zou:
Embedding for Informative Missingness: Deep Learning With Incomplete Data. Allerton 2018: 437-445 - [c18]Abubakar Abid, James Y. Zou:
A Stochastic Expectation-Maximization Approach to Shuffled Linear Regression. Allerton 2018: 470-477 - [c17]Ruishan Liu, James Zou:
The Effects of Memory Replay in Reinforcement Learning. Allerton 2018: 478-485 - [c16]Kevin Tian, Teng Zhang, James Zou:
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions. ICML 2018: 4933-4942 - [c15]Abubakar Abid, James Y. Zou:
Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders. NeurIPS 2018: 10568-10578 - [i24]Kevin Tian, Teng Zhang, James Zou:
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions. CoRR abs/1802.07839 (2018) - [i23]Abubakar Abid, James Y. Zou:
Stochastic EM for Shuffled Linear Regression. CoRR abs/1804.00681 (2018) - [i22]Anvita Gupta, James Zou:
Feedback GAN (FBGAN) for DNA: a Novel Feedback-Loop Architecture for Optimizing Protein Functions. CoRR abs/1804.01694 (2018) - [i21]Michael P. Kim, Amirata Ghorbani, James Y. Zou:
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification. CoRR abs/1805.12317 (2018) - [i20]Allen Nie, Ashley Zehnder, Rodney López Page, Arturo L. Pineda, Manuel A. Rivas, Carlos D. Bustamante, James Zou:
DeepTag: inferring all-cause diagnoses from clinical notes in under-resourced medical domain. CoRR abs/1806.10722 (2018) - [i19]Jaime Roquero Gimenez, Amirata Ghorbani, James Y. Zou:
Knockoffs for the mass: new feature importance statistics with false discovery guarantees. CoRR abs/1807.06214 (2018) - [i18]Abubakar Abid, James Y. Zou:
Autowarp: Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders. CoRR abs/1810.10107 (2018) - [i17]Jaime Roquero Gimenez, James Y. Zou:
Improving the Stability of the Knockoff Procedure: Multiple Simultaneous Knockoffs and Entropy Maximization. CoRR abs/1810.11378 (2018) - [i16]Abdi-Hakin Dirie, Abubakar Abid, James Y. Zou:
Contrastive Multivariate Singular Spectrum Analysis. CoRR abs/1810.13317 (2018) - [i15]Yuhui Zhang, Allen Nie, James Zou:
Large-scale Generative Modeling to Improve Automated Veterinary Disease Coding. CoRR abs/1811.11958 (2018) - 2017
- [c14]Aditi Raghunathan, Gregory Valiant, James Zou:
Estimating the unseen from multiple populations. ICML 2017: 2855-2863 - [c13]Pengtao Xie, Yuntian Deng, Yi Zhou, Abhimanu Kumar, Yaoliang Yu, James Zou, Eric P. Xing:
Learning Latent Space Models with Angular Constraints. ICML 2017: 3799-3810 - [c12]Fei Xia, Martin J. Zhang, James Y. Zou, David Tse:
NeuralFDR: Learning Discovery Thresholds from Hypothesis Features. NIPS 2017: 1541-1550 - [c11]Shyam Upadhyay, Kai-Wei Chang, Matt Taddy, Adam Kalai, James Y. Zou:
Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context. Rep4NLP@ACL 2017: 101-110 - [i14]Shyam Upadhyay, Kai-Wei Chang, Matt Taddy, Adam Tauman Kalai, James Y. Zou:
Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context. CoRR abs/1706.08160 (2017) - [i13]Aditi Raghunathan, Gregory Valiant, James Zou:
Estimating the unseen from multiple populations. CoRR abs/1707.03854 (2017) - [i12]Xinkun Nie, Xiaoying Tian, Jonathan Taylor, James Zou:
Why adaptively collected data have negative bias and how to correct for it. CoRR abs/1708.01977 (2017) - [i11]Abubakar Abid, Vivek Kumar Bagaria, Martin J. Zhang, James Y. Zou:
Contrastive Principal Component Analysis. CoRR abs/1709.06716 (2017) - [i10]Ruishan Liu, James Zou:
The Effects of Memory Replay in Reinforcement Learning. CoRR abs/1710.06574 (2017) - [i9]Amirata Ghorbani, Abubakar Abid, James Y. Zou:
Interpretation of Neural Networks is Fragile. CoRR abs/1710.10547 (2017) - [i8]Nikhil Garg, Londa Schiebinger, Dan Jurafsky, James Zou:
Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypes. CoRR abs/1711.08412 (2017) - 2016
- [c10]Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai:
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. NIPS 2016: 4349-4357 - [i7]Akash Srivastava, James Y. Zou, Ryan P. Adams, Charles Sutton:
Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation. CoRR abs/1602.06886 (2016) - [i6]Akash Srivastava, James Y. Zou, Ryan P. Adams, Charles Sutton:
Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation. CoRR abs/1606.05896 (2016) - [i5]Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai:
Quantifying and Reducing Stereotypes in Word Embeddings. CoRR abs/1606.06121 (2016) - [i4]Hongyao Ma, Reshef Meir, David C. Parkes, James Y. Zou:
Contingent Payment Mechanisms to Maximize Resource Utilization. CoRR abs/1607.06511 (2016) - [i3]Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Kalai:
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. CoRR abs/1607.06520 (2016) - 2015
- [j1]James Y. Zou, Eran Halperin, Esteban Gonzàlez Burchard, Sriram Sankararaman:
Inferring parental genomic ancestries using pooled semi-Markov processes. Bioinform. 31(12): 190-196 (2015) - [c9]James Y. Zou, Reshef Meir, David C. Parkes:
Strategic Voting Behavior in Doodle Polls. CSCW 2015: 464-472 - [c8]James Y. Zou, Kamalika Chaudhuri, Adam Tauman Kalai:
Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons. HCOMP 2015: 198-205 - [c7]Panos Toulis, David C. Parkes, Elery Pfeffer, James Y. Zou:
Incentive-Compatible Experimental Design. EC 2015: 285-302 - [i2]James Y. Zou, Kamalika Chaudhuri, Adam Tauman Kalai:
Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons. CoRR abs/1504.00064 (2015) - 2013
- [c6]James Y. Zou, Daniel J. Hsu, David C. Parkes, Ryan Prescott Adams:
Contrastive Learning Using Spectral Methods. NIPS 2013: 2238-2246 - 2012
- [c5]Swaprava Nath, Pankaj Dayama, Dinesh Garg, Y. Narahari, James Y. Zou:
Threats and Trade-Offs in Resource Critical Crowdsourcing Tasks Over Networks. AAAI 2012: 2447-2448 - [c4]Anders Johannson, James Y. Zou:
A Slime Mold Solver for Linear Programming Problems. CiE 2012: 344-354 - [c3]James Y. Zou, Ryan P. Adams:
Priors for Diversity in Generative Latent Variable Models. NIPS 2012: 3005-3013 - [c2]Swaprava Nath, Pankaj Dayama, Dinesh Garg, Yadati Narahari, James Y. Zou:
Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing. WINE 2012: 212-226 - [i1]Swaprava Nath, Pankaj Dayama, Dinesh Garg, Y. Narahari, James Y. Zou:
Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing. CoRR abs/1208.1676 (2012) - 2010
- [c1]James Y. Zou, Sujit Gujar, David C. Parkes:
Tolerable Manipulability in Dynamic Assignment without Money. AAAI 2010: 947-952
Coauthor Index
Sabri Eyuboglu
aka: Evan Sabri Eyuboglu
aka: Evan Sabri Eyuboglu
Tatsunori B. Hashimoto
aka: Tatsunori Hashimoto
aka: Tatsunori Hashimoto
Daniel Jurafsky
aka: Dan Jurafsky
aka: Dan Jurafsky
Serena Yeung-Levy
aka: Serena Yeung
aka: Serena Yeung
Matei Zaharia
aka: Matei A. Zaharia
aka: Matei A. Zaharia
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