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ORCIDTatsunori B. Hashimoto
Tatsunori Hashimoto – Tatsunori Benjamin Hashimoto
Person information
- affiliation: Massachusetts Institute of Technology, Department of Computer Science and Electrical Engineering
- affiliation: Harvard University, Department of Statistics
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2020 – today
- 2025
[i96]Niklas Muennighoff, Zitong Yang, Weijia Shi, Xiang Lisa Li, Li Fei-Fei, Hannaneh Hajishirzi, Luke Zettlemoyer, Percy Liang, Emmanuel J. Candès, Tatsunori Hashimoto:
s1: Simple test-time scaling. CoRR abs/2501.19393 (2025)- [i95]Xiang Lisa Li, Neil Chowdhury, Daniel D. Johnson, Tatsunori Hashimoto, Percy Liang, Sarah Schwettmann, Jacob Steinhardt:
Eliciting Language Model Behaviors with Investigator Agents. CoRR abs/2502.01236 (2025) - [i94]Martijn Bartelds, Ananjan Nandi, Moussa Koulako Bala Doumbouya, Dan Jurafsky, Tatsunori Hashimoto, Karen Livescu:
CTC-DRO: Robust Optimization for Reducing Language Disparities in Speech Recognition. CoRR abs/2502.01777 (2025) - [i93]Chenchen Gu, Xiang Lisa Li, Rohith Kuditipudi, Percy Liang, Tatsunori Hashimoto:
Auditing Prompt Caching in Language Model APIs. CoRR abs/2502.07776 (2025) - [i92]Anikait Singh, Sheryl Hsu, Kyle Hsu, Eric Mitchell, Stefano Ermon, Tatsunori Hashimoto, Archit Sharma, Chelsea Finn:
FSPO: Few-Shot Preference Optimization of Synthetic Preference Data in LLMs Elicits Effective Personalization to Real Users. CoRR abs/2502.19312 (2025) - 2024
- [j20]Tianyi Zhang, Faisal Ladhak, Esin Durmus, Percy Liang, Kathleen R. McKeown, Tatsunori B. Hashimoto:
Benchmarking Large Language Models for News Summarization. Trans. Assoc. Comput. Linguistics 12: 39-57 (2024) - [j19]Alon Albalak, Yanai Elazar, Sang Michael Xie, Shayne Longpre, Nathan Lambert, Xinyi Wang, Niklas Muennighoff, Bairu Hou, Liangming Pan, Haewon Jeong, Colin Raffel, Shiyu Chang, Tatsunori Hashimoto, William Yang Wang:
A Survey on Data Selection for Language Models. Trans. Mach. Learn. Res. 2024 (2024) - [j18]Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, Percy Liang:
Robust Distortion-free Watermarks for Language Models. Trans. Mach. Learn. Res. 2024 (2024) - [c68]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 - [c67]Vincent Grari, Thibault Laugel, Tatsunori Hashimoto, Sylvain Lamprier, Marcin Detyniecki:
On the Fairness ROAD: Robust Optimization for Adversarial Debiasing. ICLR 2024 - [c66]Chenchen Gu, Xiang Lisa Li, Percy Liang, Tatsunori Hashimoto:
On the Learnability of Watermarks for Language Models. ICLR 2024 - [c65]Xiang Lisa Li, Vaishnavi Shrivastava, Siyan Li, Tatsunori Hashimoto, Percy Liang:
Benchmarking and Improving Generator-Validator Consistency of Language Models. ICLR 2024 - [c64]Arvind V. Mahankali, Tatsunori Hashimoto, Tengyu Ma:
One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention. ICLR 2024 - [c63]Yonatan Oren, Nicole Meister, Niladri S. Chatterji, Faisal Ladhak, Tatsunori Hashimoto:
Proving Test Set Contamination in Black-Box Language Models. ICLR 2024 - [c62]Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto:
Identifying the Risks of LM Agents with an LM-Emulated Sandbox. ICLR 2024 - [c61]Neil Band, Xuechen Li, Tengyu Ma, Tatsunori Hashimoto:
Linguistic Calibration of Long-Form Generations. ICML 2024 - [c60]Ian Connick Covert, Wenlong Ji, Tatsunori Hashimoto, James Zou:
Scaling Laws for the Value of Individual Data Points in Machine Learning. ICML 2024 - [c59]Gaurav Rohit Ghosal, Tatsunori Hashimoto, Aditi Raghunathan:
Understanding Finetuning for Factual Knowledge Extraction. ICML 2024 - [c58]Christopher Mohri, Tatsunori Hashimoto:
Language Models with Conformal Factuality Guarantees. ICML 2024 - [c57]Suppakit Waiwitlikhit, Ion Stoica, Yi Sun, Tatsunori Hashimoto, Daniel Kang:
Trustless Audits without Revealing Data or Models. ICML 2024 - [c56]Qiusi Zhan, Richard Fang, Rohan Bindu, Akul Gupta, Tatsunori Hashimoto, Daniel Kang:
Removing RLHF Protections in GPT-4 via Fine-Tuning. NAACL (Short Papers) 2024: 681-687 - [c55]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 - [c54]Mingjian Jiang, Yangjun Ruan, Prasanna Sattigeri, Salim Roukos, Tatsunori B. Hashimoto:
Graph-based Uncertainty Metrics for Long-form Language Model Generations. NeurIPS 2024 - [c53]Yangjun Ruan, Chris J. Maddison, Tatsunori B. Hashimoto:
Observational Scaling Laws and the Predictability of Langauge Model Performance. NeurIPS 2024 - [c52]Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto:
Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks. SP (Workshops) 2024: 132-143 - [i91]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) - [i90]Christopher Mohri, Tatsunori Hashimoto:
Language Models with Conformal Factuality Guarantees. CoRR abs/2402.10978 (2024) - [i89]Alon Albalak, Yanai Elazar, Sang Michael Xie, Shayne Longpre, Nathan Lambert, Xinyi Wang, Niklas Muennighoff, Bairu Hou, Liangming Pan, Haewon Jeong, Colin Raffel, Shiyu Chang, Tatsunori Hashimoto, William Yang Wang:
A Survey on Data Selection for Language Models. CoRR abs/2402.16827 (2024) - [i88]Neil Band, Xuechen Li, Tengyu Ma, Tatsunori Hashimoto:
Linguistic Calibration of Language Models. CoRR abs/2404.00474 (2024) - [i87]Yann Dubois, Balázs Galambosi, Percy Liang, Tatsunori B. Hashimoto:
Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators. CoRR abs/2404.04475 (2024) - [i86]Suppakit Waiwitlikhit, Ion Stoica, Yi Sun, Tatsunori Hashimoto, Daniel Kang:
Trustless Audits without Revealing Data or Models. CoRR abs/2404.04500 (2024) - [i85]Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto:
Observational Scaling Laws and the Predictability of Language Model Performance. CoRR abs/2405.10938 (2024) - [i84]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) - [i83]Gaurav R. Ghosal, Tatsunori Hashimoto, Aditi Raghunathan:
Understanding Finetuning for Factual Knowledge Extraction. CoRR abs/2406.14785 (2024) - [i82]Yu Sun, Xinhao Li, Karan Dalal, Jiarui Xu, Arjun Vikram, Genghan Zhang, Yann Dubois, Xinlei Chen, Xiaolong Wang, Sanmi Koyejo, Tatsunori Hashimoto, Carlos Guestrin:
Learning to (Learn at Test Time): RNNs with Expressive Hidden States. CoRR abs/2407.04620 (2024) - [i81]Xiang Lisa Li, Evan Zheran Liu, Percy Liang, Tatsunori Hashimoto:
AutoBencher: Creating Salient, Novel, Difficult Datasets for Language Models. CoRR abs/2407.08351 (2024) - [i80]Shachar Don-Yehiya, Ben Burtenshaw, Ramón Fernandez Astudillo, Cailean Osborne, Mimansa Jaiswal, Tzu-Sheng Kuo, Wenting Zhao, Idan Shenfeld, Andi Peng, Mikhail Yurochkin, Atoosa Kasirzadeh, Yangsibo Huang, Tatsunori Hashimoto, Yacine Jernite, Daniel Vila-Suero, Omri Abend, Jennifer Ding, Sara Hooker, Hannah Rose Kirk, Leshem Choshen:
The Future of Open Human Feedback. CoRR abs/2408.16961 (2024) - [i79]Chenglei Si, Diyi Yang, Tatsunori Hashimoto:
Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers. CoRR abs/2409.04109 (2024) - [i78]Tristan Thrush, Christopher Potts, Tatsunori Hashimoto:
Improving Pretraining Data Using Perplexity Correlations. CoRR abs/2409.05816 (2024) - [i77]Zitong Yang, Neil Band, Shuangping Li, Emmanuel J. Candès, Tatsunori Hashimoto:
Synthetic continued pretraining. CoRR abs/2409.07431 (2024) - [i76]Ian Covert, Tony Sun, James Zou, Tatsunori Hashimoto:
Locality Alignment Improves Vision-Language Models. CoRR abs/2410.11087 (2024) - [i75]Mingjian Jiang, Yangjun Ruan, Prasanna Sattigeri, Salim Roukos, Tatsunori Hashimoto:
Graph-based Uncertainty Metrics for Long-form Language Model Outputs. CoRR abs/2410.20783 (2024) - [i74]Nicole Meister, Carlos Guestrin, Tatsunori Hashimoto:
Benchmarking Distributional Alignment of Large Language Models. CoRR abs/2411.05403 (2024) - [i73]Theodora Worledge, Tatsunori Hashimoto, Carlos Guestrin:
The Extractive-Abstractive Spectrum: Uncovering Verifiability Trade-offs in LLM Generations. CoRR abs/2411.17375 (2024) - 2023
- [j17]Clark W. Barrett, Brad Boyd, Elie Bursztein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang
, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang:
Identifying and Mitigating the Security Risks of Generative AI. Found. Trends Priv. Secur. 6(1): 1-52 (2023) - [j16]John C. Duchi, Tatsunori Hashimoto, Hongseok Namkoong:
Distributionally Robust Losses for Latent Covariate Mixtures. Oper. Res. 71(2): 649-664 (2023) - [j15]Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley, Percy Liang:
Foundation Models and Fair Use. J. Mach. Learn. Res. 24: 400:1-400:79 (2023) - [j14]Matthew Russo, Tatsunori Hashimoto, Daniel Kang, Yi Sun, Matei Zaharia:
Accelerating Aggregation Queries on Unstructured Streams of Data. Proc. VLDB Endow. 16(11): 2897-2910 (2023) - [j13]Niladri S. Chatterji, Saminul Haque, Tatsunori Hashimoto:
Undersampling is a Minimax Optimal Robustness Intervention in Nonparametric Classification. Trans. Mach. Learn. Res. 2023 (2023) - [j12]Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda:
Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. 2023 (2023) - [c51]Tianyi Zhang, Mina Lee, Xiang Lisa Li, Ende Shen, Tatsunori Hashimoto:
TempLM: Distilling Language Models into Template-Based Generators. ACL (Findings) 2023: 1970-1994 - [c50]Fatemehsadat Mireshghallah, Yu Su, Tatsunori Hashimoto, Jason Eisner, Richard Shin:
Privacy-Preserving Domain Adaptation of Semantic Parsers. ACL (1) 2023: 4950-4970 - [c49]Faisal Ladhak, Esin Durmus, Tatsunori Hashimoto:
Contrastive Error Attribution for Finetuned Language Models. ACL (1) 2023: 11482-11498 - [c48]Xiang Lisa Li, Ari Holtzman, Daniel Fried, Percy Liang, Jason Eisner, Tatsunori Hashimoto, Luke Zettlemoyer, Mike Lewis:
Contrastive Decoding: Open-ended Text Generation as Optimization. ACL (1) 2023: 12286-12312 - [c47]Faisal Ladhak, Esin Durmus, Mirac Suzgun, Tianyi Zhang, Dan Jurafsky, Kathleen R. McKeown, Tatsunori Hashimoto:
When Do Pre-Training Biases Propagate to Downstream Tasks? A Case Study in Text Summarization. EACL 2023: 3198-3211 - [c46]Kaitlyn Zhou, Dan Jurafsky, Tatsunori Hashimoto:
Navigating the Grey Area: How Expressions of Uncertainty and Overconfidence Affect Language Models. EMNLP 2023: 5506-5524 - [c45]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 - [c44]Shibani Santurkar, Yann Dubois, Rohan Taori, Percy Liang, Tatsunori Hashimoto:
Is a Caption Worth a Thousand Images? A Study on Representation Learning. ICLR 2023 - [c43]Yann Dubois, Tatsunori Hashimoto, Percy Liang:
Evaluating Self-Supervised Learning via Risk Decomposition. ICML 2023: 8779-8820 - [c42]Irena Gao, Shiori Sagawa, Pang Wei Koh, Tatsunori Hashimoto, Percy Liang:
Out-of-Domain Robustness via Targeted Augmentations. ICML 2023: 10800-10834 - [c41]Shibani Santurkar, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, Tatsunori Hashimoto:
Whose Opinions Do Language Models Reflect? ICML 2023: 29971-30004 - [c40]Rohan Taori, Tatsunori Hashimoto:
Data Feedback Loops: Model-driven Amplification of Dataset Biases. ICML 2023: 33883-33920 - [c39]Tianyi Zhang, Tao Yu, Tatsunori Hashimoto, Mike Lewis, Wen-Tau Yih, Daniel Fried, Sida Wang:
Coder Reviewer Reranking for Code Generation. ICML 2023: 41832-41846 - [c38]Pratiksha Thaker, Matei Zaharia, Tatsunori Hashimoto:
Congestion Control Safety via Comparative Statics. INFOCOM 2023: 1-10 - [c37]Yann Dubois, Chen Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto:
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. NeurIPS 2023 - [c36]Ishaan Gulrajani, Tatsunori B. Hashimoto:
Likelihood-Based Diffusion Language Models. NeurIPS 2023 - [c35]Allen Nie, Yuhui Zhang, Atharva Amdekar, Chris Piech, Tatsunori B. Hashimoto, Tobias Gerstenberg:
MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks. NeurIPS 2023 - [i72]Tianyi Zhang, Faisal Ladhak, Esin Durmus, Percy Liang, Kathleen R. McKeown, Tatsunori B. Hashimoto:
Benchmarking Large Language Models for News Summarization. CoRR abs/2301.13848 (2023) - [i71]Yann Dubois, Tatsunori Hashimoto, Percy Liang:
Evaluating Self-Supervised Learning via Risk Decomposition. CoRR abs/2302.03068 (2023) - [i70]Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto:
Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks. CoRR abs/2302.05733 (2023) - [i69]Irena Gao, Shiori Sagawa, Pang Wei Koh, Tatsunori Hashimoto, Percy Liang:
Out-of-Domain Robustness via Targeted Augmentations. CoRR abs/2302.11861 (2023) - [i68]Kaitlyn Zhou, Dan Jurafsky, Tatsunori Hashimoto:
Navigating the Grey Area: Expressions of Overconfidence and Uncertainty in Language Models. CoRR abs/2302.13439 (2023) - [i67]Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley, Percy Liang:
Foundation Models and Fair Use. CoRR abs/2303.15715 (2023) - [i66]Shibani Santurkar, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, Tatsunori Hashimoto:
Whose Opinions Do Language Models Reflect? CoRR abs/2303.17548 (2023) - [i65]Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto:
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. CoRR abs/2305.14387 (2023) - [i64]Ishaan Gulrajani, Tatsunori B. Hashimoto:
Likelihood-Based Diffusion Language Models. CoRR abs/2305.18619 (2023) - [i63]Arvind V. Mahankali, Tatsunori B. Hashimoto, Tengyu Ma:
One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention. CoRR abs/2307.03576 (2023) - [i62]Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, Percy Liang:
Robust Distortion-free Watermarks for Language Models. CoRR abs/2307.15593 (2023) - [i61]Peter Henderson, Tatsunori Hashimoto, Mark A. Lemley:
Where's the Liability in Harmful AI Speech? CoRR abs/2308.04635 (2023) - [i60]Matthew Russo, Tatsunori Hashimoto, Daniel Kang, Yi Sun, Matei Zaharia:
Accelerating Aggregation Queries on Unstructured Streams of Data. CoRR abs/2308.09157 (2023) - [i59]Clark W. Barrett, Brad Boyd, Ellie Burzstein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang:
Identifying and Mitigating the Security Risks of Generative AI. CoRR abs/2308.14840 (2023) - [i58]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) - [i57]Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto:
Identifying the Risks of LM Agents with an LM-Emulated Sandbox. CoRR abs/2309.15817 (2023) - [i56]Xiang Lisa Li, Vaishnavi Shrivastava, Siyan Li, Tatsunori Hashimoto, Percy Liang:
Benchmarking and Improving Generator-Validator Consistency of Language Models. CoRR abs/2310.01846 (2023) - [i55]Yu Sun, Xinhao Li, Karan Dalal, Chloe Hsu, Sanmi Koyejo, Carlos Guestrin, Xiaolong Wang, Tatsunori Hashimoto, Xinlei Chen:
Learning to (Learn at Test Time). CoRR abs/2310.13807 (2023) - [i54]Yonatan Oren, Nicole Meister, Niladri S. Chatterji, Faisal Ladhak, Tatsunori B. Hashimoto:
Proving Test Set Contamination in Black Box Language Models. CoRR abs/2310.17623 (2023) - [i53]Vincent Grari, Thibault Laugel, Tatsunori Hashimoto, Sylvain Lamprier, Marcin Detyniecki:
On the Fairness ROAD: Robust Optimization for Adversarial Debiasing. CoRR abs/2310.18413 (2023) - [i52]Allen Nie, Yuhui Zhang, Atharva Amdekar, Chris Piech, Tatsunori Hashimoto, Tobias Gerstenberg:
MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks. CoRR abs/2310.19677 (2023) - [i51]Qiusi Zhan, Richard Fang, Rohan Bindu, Akul Gupta, Tatsunori Hashimoto, Daniel Kang:
Removing RLHF Protections in GPT-4 via Fine-Tuning. CoRR abs/2311.05553 (2023) - [i50]Jiayi Li, Rohan Taori, Tatsunori B. Hashimoto:
Benchmarking Multi-Domain Active Learning on Image Classification. CoRR abs/2312.00364 (2023) - [i49]Chenchen Gu, Xiang Lisa Li, Percy Liang, Tatsunori Hashimoto:
On the Learnability of Watermarks for Language Models. CoRR abs/2312.04469 (2023) - 2022
- [j11]Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus:
Emergent Abilities of Large Language Models. Trans. Mach. Learn. Res. 2022 (2022) - [c34]Esin Durmus, Faisal Ladhak, Tatsunori Hashimoto:
Spurious Correlations in Reference-Free Evaluation of Text Generation. ACL (1) 2022: 1443-1454 - [c33]Mitchell L. Gordon, Michelle S. Lam, Joon Sung Park, Kayur Patel, Jeffrey T. Hancock, Tatsunori Hashimoto, Michael S. Bernstein:
Jury Learning: Integrating Dissenting Voices into Machine Learning Models. CHI 2022: 115:1-115:19 - [c32]Xuechen Li, Florian Tramèr, Percy Liang, Tatsunori Hashimoto:
Large Language Models Can Be Strong Differentially Private Learners. ICLR 2022 - [c31]Paul Michel, Tatsunori Hashimoto, Graham Neubig:
Distributionally Robust Models with Parametric Likelihood Ratios. ICLR 2022 - [c30]Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang:
Extending the WILDS Benchmark for Unsupervised Adaptation. ICLR 2022 - [c29]Ke Alexander Wang, Niladri Shekhar Chatterji, Saminul Haque, Tatsunori Hashimoto:
Is Importance Weighting Incompatible with Interpolating Classifiers? ICLR 2022 - [c28]Rose E. Wang, Esin Durmus, Noah D. Goodman, Tatsunori Hashimoto:
Language modeling via stochastic processes. ICLR 2022 - [c27]Ishaan Gulrajani, Tatsunori Hashimoto:
Identifiability Conditions for Domain Adaptation. ICML 2022: 7982-7997 - [c26]Yann Dubois, Stefano Ermon, Tatsunori B. Hashimoto, Percy Liang:
Improving Self-Supervised Learning by Characterizing Idealized Representations. NeurIPS 2022 - [c25]Xuechen Li, Daogao Liu, Tatsunori B. Hashimoto, Huseyin A. Inan, Janardhan Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta:
When Does Differentially Private Learning Not Suffer in High Dimensions? NeurIPS 2022 - [c24]Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B. Hashimoto:
Diffusion-LM Improves Controllable Text Generation. NeurIPS 2022 - [c23]Tong Mu, Yash Chandak, Tatsunori B. Hashimoto, Emma Brunskill:
Factored DRO: Factored Distributionally Robust Policies for Contextual Bandits. NeurIPS 2022 - [c22]Daniel Kang, John Guibas, Peter D. Bailis, Tatsunori Hashimoto, Matei Zaharia:
TASTI: Semantic Indexes for Machine Learning-based Queries over Unstructured Data. SIGMOD Conference 2022: 1934-1947 - [i48]Mitchell L. Gordon, Michelle S. Lam, Joon Sung Park, Kayur Patel, Jeffrey T. Hancock, Tatsunori Hashimoto, Michael S. Bernstein:
Jury Learning: Integrating Dissenting Voices into Machine Learning Models. CoRR abs/2202.02950 (2022) - [i47]Rose E. Wang, Esin Durmus, Noah D. Goodman, Tatsunori Hashimoto:
Language modeling via stochastic processes. CoRR abs/2203.11370 (2022) - [i46]Paul Michel, Tatsunori Hashimoto, Graham Neubig:
Distributionally Robust Models with Parametric Likelihood Ratios. CoRR abs/2204.06340 (2022) - [i45]Esin Durmus, Faisal Ladhak, Tatsunori Hashimoto:
Spurious Correlations in Reference-Free Evaluation of Text Generation. CoRR abs/2204.09890 (2022) - [i44]Tianyi Zhang, Mina Lee, Lisa Li, Ende Shen, Tatsunori B. Hashimoto:
TempLM: Distilling Language Models into Template-Based Generators. CoRR abs/2205.11055 (2022) - [i43]Niladri S. Chatterji, Saminul Haque, Tatsunori Hashimoto:
Undersampling is a Minimax Optimal Robustness Intervention in Nonparametric Classification. CoRR abs/2205.13094 (2022) - [i42]Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B. Hashimoto:
Diffusion-LM Improves Controllable Text Generation. CoRR abs/2205.14217 (2022) - [i41]Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus:
Emergent Abilities of Large Language Models. CoRR abs/2206.07682 (2022) - [i40]Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin A. Inan, Janardhan Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta:
When Does Differentially Private Learning Not Suffer in High Dimensions? CoRR abs/2207.00160 (2022) - [i39]Shibani Santurkar, Yann Dubois, Rohan Taori, Percy Liang, Tatsunori Hashimoto:
Is a Caption Worth a Thousand Images? A Controlled Study for Representation Learning. CoRR abs/2207.07635 (2022) - [i38]Rohan Taori, Tatsunori B. Hashimoto:
Data Feedback Loops: Model-driven Amplification of Dataset Biases. CoRR abs/2209.03942 (2022) - [i37]Yann Dubois, Tatsunori Hashimoto, Stefano Ermon, Percy Liang:
Improving Self-Supervised Learning by Characterizing Idealized Representations. CoRR abs/2209.06235 (2022) - [i36]Hanlin Zhang, Xuechen Li, Prithviraj Sen, Salim Roukos, Tatsunori Hashimoto:
A Closer Look at the Calibration of Differentially Private Learners. CoRR abs/2210.08248 (2022) - [i35]Daniel Kang, Tatsunori Hashimoto, Ion Stoica, Yi Sun:
Scaling up Trustless DNN Inference with Zero-Knowledge Proofs. CoRR abs/2210.08674 (2022) - [i34]Xiang Lisa Li, Ari Holtzman, Daniel Fried, Percy Liang, Jason Eisner, Tatsunori Hashimoto, Luke Zettlemoyer, Mike Lewis:
Contrastive Decoding: Open-ended Text Generation as Optimization. CoRR abs/2210.15097 (2022) - [i33]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) - [i32]Daniel Kang, Tatsunori Hashimoto, Ion Stoica, Yi Sun:
ZK-IMG: Attested Images via Zero-Knowledge Proofs to Fight Disinformation. CoRR abs/2211.04775 (2022) - [i31]Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda:
Holistic Evaluation of Language Models. CoRR abs/2211.09110 (2022) - [i30]Tianyi Zhang, Tao Yu, Tatsunori B. Hashimoto, Mike Lewis, Wen-tau Yih, Daniel Fried, Sida I. Wang:
Coder Reviewer Reranking for Code Generation. CoRR abs/2211.16490 (2022) - [i29]Fatemehsadat Mireshghallah, Richard Shin, Yu Su, Tatsunori Hashimoto, Jason Eisner:
Privacy-Preserving Domain Adaptation of Semantic Parsers. CoRR abs/2212.10520 (2022) - [i28]Faisal Ladhak, Esin Durmus, Tatsunori Hashimoto:
Tracing and Removing Data Errors in Natural Language Generation Datasets. CoRR abs/2212.10722 (2022) - 2021
- [j10]Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Yi Sun, Matei Zaharia:
Accelerating Approximate Aggregation Queries with Expensive Predicates. Proc. VLDB Endow. 14(11): 2341-2354 (2021) - [c21]Dorottya Demszky, Jing Liu, Zid Mancenido, Julie Cohen, Heather Hill, Dan Jurafsky, Tatsunori Hashimoto:
Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions. ACL/IJCNLP (1) 2021: 1638-1653 - [c20]Mitchell L. Gordon, Kaitlyn Zhou, Kayur Patel, Tatsunori Hashimoto, Michael S. Bernstein:
The Disagreement Deconvolution: Bringing Machine Learning Performance Metrics In Line With Reality. CHI 2021: 388:1-388:14 - [c19]Pratiksha Thaker, Matei Zaharia, Tatsunori Hashimoto:
Don't Hate the Player, Hate the Game: Safety and Utility in Multi-Agent Congestion Control. HotNets 2021: 140-146 - [c18]Paul Michel, Tatsunori Hashimoto, Graham Neubig:
Modeling the Second Player in Distributionally Robust Optimization. ICLR 2021 - [c17]Tatsunori Hashimoto:
Model Performance Scaling with Multiple Data Sources. ICML 2021: 4107-4116 - [c16]Shikhar Murty, Tatsunori Hashimoto, Christopher D. Manning:
DReCa: A General Task Augmentation Strategy for Few-Shot Natural Language Inference. NAACL-HLT 2021: 1113-1125 - [c15]Tianyi Zhang, Tatsunori Hashimoto:
On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies. NAACL-HLT 2021: 5131-5146 - [i27]Sebastian Gehrmann, Tosin P. Adewumi, Karmanya Aggarwal, Pawan Sasanka Ammanamanchi, Aremu Anuoluwapo, Antoine Bosselut, Khyathi Raghavi Chandu, Miruna-Adriana Clinciu, Dipanjan Das, Kaustubh D. Dhole, Wanyu Du, Esin Durmus, Ondrej Dusek, Chris Emezue, Varun Gangal, Cristina Garbacea, Tatsunori Hashimoto, Yufang Hou, Yacine Jernite, Harsh Jhamtani, Yangfeng Ji, Shailza Jolly, Dhruv Kumar, Faisal Ladhak, Aman Madaan, Mounica Maddela, Khyati Mahajan, Saad Mahamood, Bodhisattwa Prasad Majumder, Pedro Henrique Martins, Angelina McMillan-Major, Simon Mille, Emiel van Miltenburg, Moin Nadeem, Shashi Narayan, Vitaly Nikolaev, Rubungo Andre Niyongabo, Salomey Osei, Ankur P. Parikh, Laura Perez-Beltrachini, Niranjan Ramesh Rao, Vikas Raunak, Juan Diego Rodriguez, Sashank Santhanam, João Sedoc, Thibault Sellam, Samira Shaikh, Anastasia Shimorina, Marco Antonio Sobrevilla Cabezudo, Hendrik Strobelt, Nishant Subramani, Wei Xu, Diyi Yang, Akhila Yerukola, Jiawei Zhou:
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics. CoRR abs/2102.01672 (2021) - [i26]Paul Michel, Tatsunori Hashimoto, Graham Neubig:
Modeling the Second Player in Distributionally Robust Optimization. CoRR abs/2103.10282 (2021) - [i25]Tianyi Zhang, Tatsunori Hashimoto:
On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies. CoRR abs/2104.05694 (2021) - [i24]Dorottya Demszky, Jing Liu, Zid Mancenido, Julie Cohen, Heather Hill, Dan Jurafsky, Tatsunori Hashimoto:
Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions. CoRR abs/2106.03873 (2021) - [i23]Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Yi Sun, Matei Zaharia:
Proof: Accelerating Approximate Aggregation Queries with Expensive Predicates. CoRR abs/2107.12525 (2021) - [i22]Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Yi Sun, Matei Zaharia:
Accelerating Approximate Aggregation Queries with Expensive Predicates. CoRR abs/2108.06313 (2021) - [i21]Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren E. Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.:
On the Opportunities and Risks of Foundation Models. CoRR abs/2108.07258 (2021) - [i20]Xuechen Li, Florian Tramèr, Percy Liang, Tatsunori Hashimoto:
Large Language Models Can Be Strong Differentially Private Learners. CoRR abs/2110.05679 (2021) - [i19]Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang:
Extending the WILDS Benchmark for Unsupervised Adaptation. CoRR abs/2112.05090 (2021) - [i18]Ke Alexander Wang, Niladri S. Chatterji, Saminul Haque, Tatsunori Hashimoto:
Is Importance Weighting Incompatible with Interpolating Classifiers? CoRR abs/2112.12986 (2021) - 2020
- [j9]Daniel Kang, Edward Gan, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia:
Approximate Selection with Guarantees using Proxies. Proc. VLDB Endow. 13(11): 1990-2003 (2020) - [c14]Daniel Kang, Tatsunori Hashimoto:
Improved Natural Language Generation via Loss Truncation. ACL 2020: 718-731 - [c13]Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, Percy Liang:
Distributionally Robust Neural Networks. ICLR 2020 - [c12]Megha Srivastava, Tatsunori B. Hashimoto, Percy Liang:
Robustness to Spurious Correlations via Human Annotations. ICML 2020: 9109-9119 - [i17]Daniel Kang, Edward Gan, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia:
Approximate Selection with Guarantees using Proxies. CoRR abs/2004.00827 (2020) - [i16]Daniel Kang, Tatsunori Hashimoto:
Improved Natural Language Generation via Loss Truncation. CoRR abs/2004.14589 (2020) - [i15]Megha Srivastava, Tatsunori B. Hashimoto, Percy Liang:
Robustness to Spurious Correlations via Human Annotations. CoRR abs/2007.06661 (2020) - [i14]John C. Duchi, Tatsunori Hashimoto, Hongseok Namkoong:
Distributionally Robust Losses for Latent Covariate Mixtures. CoRR abs/2007.13982 (2020) - [i13]Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia:
Task-agnostic Indexes for Deep Learning-based Queries over Unstructured Data. CoRR abs/2009.04540 (2020)
2010 – 2019
- 2019
- [c11]Emma Pierson, Pang Wei Koh, Tatsunori B. Hashimoto, Daphne Koller, Jure Leskovec, Nick Eriksson, Percy Liang:
Inferring Multidimensional Rates of Aging from Cross-Sectional Data. AISTATS 2019: 97-107 - [c10]Yonatan Oren, Shiori Sagawa, Tatsunori B. Hashimoto, Percy Liang:
Distributionally Robust Language Modeling. EMNLP/IJCNLP (1) 2019: 4226-4236 - [c9]Tatsunori B. Hashimoto, Hugh Zhang, Percy Liang:
Unifying Human and Statistical Evaluation for Natural Language Generation. NAACL-HLT (1) 2019: 1689-1701 - [i12]Tatsunori B. Hashimoto, Hugh Zhang, Percy Liang:
Unifying Human and Statistical Evaluation for Natural Language Generation. CoRR abs/1904.02792 (2019) - [i11]Yonatan Oren, Shiori Sagawa, Tatsunori B. Hashimoto, Percy Liang:
Distributionally Robust Language Modeling. CoRR abs/1909.02060 (2019) - [i10]Mina Lee, Tatsunori B. Hashimoto, Percy Liang:
Learning Autocomplete Systems as a Communication Game. CoRR abs/1911.06964 (2019) - [i9]Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, Percy Liang:
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization. CoRR abs/1911.08731 (2019) - 2018
- [j8]Kelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, Percy Liang:
Generating Sentences by Editing Prototypes. Trans. Assoc. Comput. Linguistics 6: 437-450 (2018) - [c8]Tatsunori Hashimoto, Steve Yadlowsky, John C. Duchi:
Derivative Free Optimization Via Repeated Classification. AISTATS 2018: 2027-2036 - [c7]Tatsunori B. Hashimoto, Megha Srivastava, Hongseok Namkoong, Percy Liang:
Fairness Without Demographics in Repeated Loss Minimization. ICML 2018: 1934-1943 - [c6]Tatsunori B. Hashimoto, Kelvin Guu, Yonatan Oren, Percy Liang:
A Retrieve-and-Edit Framework for Predicting Structured Outputs. NeurIPS 2018: 10073-10083 - [i8]Tatsunori B. Hashimoto, Steve Yadlowsky, John C. Duchi:
Derivative free optimization via repeated classification. CoRR abs/1804.03761 (2018) - [i7]Tatsunori B. Hashimoto, Megha Srivastava, Hongseok Namkoong, Percy Liang:
Fairness Without Demographics in Repeated Loss Minimization. CoRR abs/1806.08010 (2018) - [i6]Emma Pierson, Pang Wei Koh, Tatsunori B. Hashimoto, Daphne Koller, Jure Leskovec, Nicholas Eriksson, Percy Liang:
Inferring Multi-Dimensional Rates of Aging from Cross-Sectional Data. CoRR abs/1807.04709 (2018) - [i5]Tatsunori B. Hashimoto, Kelvin Guu, Yonatan Oren, Percy Liang:
A Retrieve-and-Edit Framework for Predicting Structured Outputs. CoRR abs/1812.01194 (2018) - 2017
- [c5]Tatsunori B. Hashimoto, Percy Liang, John C. Duchi:
Unsupervised Transformation Learning via Convex Relaxations. NIPS 2017: 6875-6883 - [i4]Kelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, Percy Liang:
Generating Sentences by Editing Prototypes. CoRR abs/1709.08878 (2017) - 2016
- [b1]Tatsunori Benjamin Hashimoto:
Continuous representations and models from random walk diffusion limits. Massachusetts Institute of Technology, Cambridge, USA, 2016 - [j7]Haoyang Zeng, Tatsunori B. Hashimoto, Daniel D. Kang, David K. Gifford:
GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding. Bioinform. 32(4): 490-496 (2016) - [j6]Tatsunori B. Hashimoto, David Alvarez-Melis, Tommi S. Jaakkola:
Word Embeddings as Metric Recovery in Semantic Spaces. Trans. Assoc. Comput. Linguistics 4: 273-286 (2016) - [c4]Tatsunori B. Hashimoto, David K. Gifford, Tommi S. Jaakkola:
Learning Population-Level Diffusions with Generative RNNs. ICML 2016: 2417-2426 - 2015
- [c3]Tatsunori B. Hashimoto, Yi Sun, Tommi S. Jaakkola:
Metric recovery from directed unweighted graphs. AISTATS 2015 - [c2]Tatsunori B. Hashimoto, Yi Sun, Tommi S. Jaakkola:
From random walks to distances on unweighted graphs. NIPS 2015: 3429-3437 - [i3]Tatsunori B. Hashimoto, David Alvarez-Melis, Tommi S. Jaakkola:
Word, graph and manifold embedding from Markov processes. CoRR abs/1509.05808 (2015) - [i2]Tatsunori B. Hashimoto, Yi Sun, Tommi S. Jaakkola:
From random walks to distances on unweighted graphs. CoRR abs/1511.00573 (2015) - 2014
- [j5]Tatsunori B. Hashimoto, Matthew D. Edwards, David K. Gifford:
Universal Count Correction for High-Throughput Sequencing. PLoS Comput. Biol. 10(3) (2014) - [i1]Tatsunori B. Hashimoto, Yi Sun, Tommi S. Jaakkola:
Metric recovery from directed unweighted graphs. CoRR abs/1411.5720 (2014) - 2012
- [j4]Tatsunori B. Hashimoto, Tommi S. Jaakkola, Richard Sherwood, Esteban O. Mazzoni, Hynek Wichterle, David K. Gifford:
Lineage-based identification of cellular states and expression programs. Bioinform. 28(12): 250-257 (2012) - 2011
- [c1]Albert Shieh, Tatsunori B. Hashimoto, Edoardo M. Airoldi:
Tree preserving embedding. ICML 2011: 753-760
2000 – 2009
- 2009
- [j3]Tatsunori B. Hashimoto, Masao Nagasaki, Kaname Kojima, Satoru Miyano:
BFL: a node and edge betweenness based fast layout algorithm for large scale networks. BMC Bioinform. 10 (2009) - [j2]Tamio Kawaguchi, Noritsugu Shiokawa, Kohei Nakayama, Takatoshi Watanabe, Tatsunori Hashimoto, Hiroyuki Kayano:
Superconducting Narrowband Filter for Receiver of Weather Radar. IEICE Trans. Electron. 92-C(3): 296-301 (2009) - 2005
- [j1]Hiroyuki Kayano, Hiroyuki Fuke, Fumihiko Aiga, Mutsuki Yamazaki, Yoshiaki Terashima, Tatsunori Hashimoto:
Electrically Tunable Superconducting Microstrip Line Band-Pass Filter for Mobile Applications. IEICE Trans. Electron. 88-C(2): 221-225 (2005)
Coauthor Index
Niladri S. Chatterji
aka: Niladri Shekhar Chatterji
aka: Niladri Shekhar Chatterji
Daniel Jurafsky
aka: Dan Jurafsky
aka: Dan Jurafsky
Xiang Li 0063
aka: Xiang Lisa Li
aka: Xiang Lisa Li
[i96] [i95] [i93] [j20] [j18] [c66] [c65] [i87] [i81] [j15] [j12] [c48] [c44] [c43] [c42] [c41] [c37] [i72] [i71] [i69] [i67] [i66] [i65] [i62] [i56] [i49] [j11] [c32] [c30] [c26] [c24] [i42] [i41] [i39] [i37] [i34] [i31] [i20] [i19] [c13] [c12] [i15] [c11] [c10] [c9] [i12] [i11] [i10] [i9] [j8] [c7] [c6] [i7] [i6] [i5] [c5] [i4]
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