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2020 – today
- 2022
[j2]Caihong Mu, Weizhu Chen, Yi Liu
, Dongchang Lei, Ruochen Liu:
Virtual information core optimization for collaborative filtering recommendation based on clustering and evolutionary algorithms. Appl. Soft Comput. 116: 108355 (2022)- [c63]Zhuocheng Gong, Di He, Yelong Shen, Tie-Yan Liu, Weizhu Chen, Dongyan Zhao, Ji-Rong Wen, Rui Yan:
Finding the Dominant Winning Ticket in Pre-Trained Language Models. ACL (Findings) 2022: 1459-1472 - [c62]Woojeong Jin, Yu Cheng, Yelong Shen, Weizhu Chen, Xiang Ren:
A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models. ACL (1) 2022: 2763-2775 - [c61]Jing Qian, Li Dong, Yelong Shen, Furu Wei, Weizhu Chen:
Controllable Natural Language Generation with Contrastive Prefixes. ACL (Findings) 2022: 2912-2924 - [c60]Wei Chen, Yeyun Gong, Song Wang, Bolun Yao, Weizhen Qi, Zhongyu Wei, Xiaowu Hu, Bartuer Zhou, Yi Mao, Weizhu Chen, Biao Cheng, Nan Duan:
DialogVED: A Pre-trained Latent Variable Encoder-Decoder Model for Dialog Response Generation. ACL (1) 2022: 4852-4864 - [c59]Tianyu Liu, Yizhe Zhang, Chris Brockett, Yi Mao, Zhifang Sui, Weizhu Chen, Bill Dolan:
A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation. ACL (1) 2022: 6723-6737 - [c58]Chen Liang, Pengcheng He, Yelong Shen, Weizhu Chen, Tuo Zhao:
CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing. ACL (1) 2022: 7162-7175 - [c57]Jiachang Liu, Dinghan Shen, Yizhe Zhang, Bill Dolan, Lawrence Carin, Weizhu Chen:
What Makes Good In-Context Examples for GPT-3? DeeLIO@ACL 2022: 100-114 - [i63]Xiaonan Li, Yeyun Gong, Yelong Shen, Xipeng Qiu, Hang Zhang, Bolun Yao, Weizhen Qi, Daxin Jiang, Weizhu Chen, Nan Duan:
CodeRetriever: Unimodal and Bimodal Contrastive Learning. CoRR abs/2201.10866 (2022) - [i62]Xinyu Pi, Qian Liu, Bei Chen, Morteza Ziyadi, Zeqi Lin, Yan Gao, Qiang Fu, Jian-Guang Lou, Weizhu Chen:
Reasoning Like Program Executors. CoRR abs/2201.11473 (2022) - [i61]Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. CoRR abs/2202.02664 (2022) - [i60]Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
Mixing and Shifting: Exploiting Global and Local Dependencies in Vision MLPs. CoRR abs/2202.06510 (2022) - [i59]Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
Truncated Diffusion Probabilistic Models. CoRR abs/2202.09671 (2022) - [i58]Jing Qian, Li Dong, Yelong Shen, Furu Wei, Weizhu Chen:
Controllable Natural Language Generation with Contrastive Prefixes. CoRR abs/2202.13257 (2022) - [i57]Shengnan An, Yifei Li, Zeqi Lin, Qian Liu, Bei Chen, Qiang Fu, Weizhu Chen, Nanning Zheng, Jian-Guang Lou:
Input-Tuning: Adapting Unfamiliar Inputs to Frozen Pretrained Models. CoRR abs/2203.03131 (2022) - [i56]Greg Yang, Edward J. Hu, Igor Babuschkin, Szymon Sidor, Xiaodong Liu, David Farhi, Nick Ryder, Jakub Pachocki, Weizhu Chen, Jianfeng Gao:
Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer. CoRR abs/2203.03466 (2022) - [i55]Chen Liang, Pengcheng He, Yelong Shen, Weizhu Chen, Tuo Zhao:
CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing. CoRR abs/2204.06625 (2022) - [i54]Simiao Zuo, Qingru Zhang, Chen Liang, Pengcheng He, Tuo Zhao, Weizhu Chen:
MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation. CoRR abs/2204.07675 (2022) - [i53]Wei Chen, Yeyun Gong, Song Wang, Bolun Yao, Weizhen Qi, Zhongyu Wei, Xiaowu Hu, Bartuer Zhou, Yi Mao, Weizhu Chen, Biao Cheng, Nan Duan:
DialogVED: A Pre-trained Latent Variable Encoder-Decoder Model for Dialog Response Generation. CoRR abs/2204.13031 (2022) - [i52]Shujian Zhang, Chengyue Gong, Xingchao Liu, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
ALLSH: Active Learning Guided by Local Sensitivity and Hardness. CoRR abs/2205.04980 (2022) - [i51]Weizhen Qi, Yeyun Gong, Yelong Shen, Jian Jiao, Yu Yan, Houqiang Li, Ruofei Zhang, Weizhu Chen, Nan Duan:
A Self-Paced Mixed Distillation Method for Non-Autoregressive Generation. CoRR abs/2205.11162 (2022) - [i50]Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
Diffusion-GAN: Training GANs with Diffusion. CoRR abs/2206.02262 (2022) - [i49]Yifei Li, Zeqi Lin, Shizhuo Zhang, Qiang Fu, Bei Chen, Jian-Guang Lou, Weizhu Chen:
On the Advance of Making Language Models Better Reasoners. CoRR abs/2206.02336 (2022) - [i48]Daoguang Zan, Bei Chen, Dejian Yang, Zeqi Lin, Minsu Kim, Bei Guan, Yongji Wang, Weizhu Chen, Jian-Guang Lou:
CERT: Continual Pre-Training on Sketches for Library-Oriented Code Generation. CoRR abs/2206.06888 (2022) - 2021
- [c56]Yuning Mao, Pengcheng He, Xiaodong Liu, Yelong Shen, Jianfeng Gao, Jiawei Han, Weizhu Chen:
Reader-Guided Passage Reranking for Open-Domain Question Answering. ACL/IJCNLP (Findings) 2021: 344-350 - [c55]Dayiheng Liu, Yu Yan, Yeyun Gong, Weizhen Qi, Hang Zhang, Jian Jiao, Weizhu Chen, Jie Fu, Linjun Shou, Ming Gong, Pengcheng Wang, Jiusheng Chen, Daxin Jiang, Jiancheng Lv, Ruofei Zhang, Winnie Wu, Ming Zhou, Nan Duan:
GLGE: A New General Language Generation Evaluation Benchmark. ACL/IJCNLP (Findings) 2021: 408-420 - [c54]Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao:
UnitedQA: A Hybrid Approach for Open Domain Question Answering. ACL/IJCNLP (1) 2021: 3080-3090 - [c53]Yuning Mao, Pengcheng He, Xiaodong Liu, Yelong Shen, Jianfeng Gao, Jiawei Han, Weizhu Chen:
Generation-Augmented Retrieval for Open-Domain Question Answering. ACL/IJCNLP (1) 2021: 4089-4100 - [c52]Yuekai Zhao, Li Dong, Yelong Shen, Zhihua Zhang, Furu Wei, Weizhu Chen:
Memory-Efficient Differentiable Transformer Architecture Search. ACL/IJCNLP (Findings) 2021: 4254-4264 - [c51]Jiaao Chen, Dinghan Shen, Weizhu Chen, Diyi Yang:
HiddenCut: Simple Data Augmentation for Natural Language Understanding with Better Generalizability. ACL/IJCNLP (1) 2021: 4380-4390 - [c50]Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen:
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. ACL/IJCNLP (1) 2021: 6524-6538 - [c49]Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Tuo Zhao:
Token-wise Curriculum Learning for Neural Machine Translation. EMNLP (Findings) 2021: 3658-3670 - [c48]Simiao Zuo, Chen Liang, Haoming Jiang, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
ARCH: Efficient Adversarial Regularized Training with Caching. EMNLP (Findings) 2021: 4118-4131 - [c47]Simiao Zuo, Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach. EMNLP (1) 2021: 6562-6577 - [c46]Jiaxin Huang, Chunyuan Li, Krishan Subudhi, Damien Jose, Shobana Balakrishnan, Weizhu Chen, Baolin Peng, Jianfeng Gao, Jiawei Han:
Few-Shot Named Entity Recognition: An Empirical Baseline Study. EMNLP (1) 2021: 10408-10423 - [c45]Jungo Kasai, Hao Peng, Yizhe Zhang, Dani Yogatama, Gabriel Ilharco, Nikolaos Pappas, Yi Mao, Weizhu Chen, Noah A. Smith:
Finetuning Pretrained Transformers into RNNs. EMNLP (1) 2021: 10630-10643 - [c44]Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen:
Deberta: decoding-Enhanced Bert with Disentangled Attention. ICLR 2021 - [c43]Kevin J. Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin:
MixKD: Towards Efficient Distillation of Large-scale Language Models. ICLR 2021 - [c42]Yanru Qu, Dinghan Shen, Yelong Shen, Sandra Sajeev, Weizhu Chen, Jiawei Han:
CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding. ICLR 2021 - [c41]Weizhen Qi, Yeyun Gong, Jian Jiao, Yu Yan, Weizhu Chen, Dayiheng Liu, Kewen Tang, Houqiang Li, Jiusheng Chen, Ruofei Zhang, Ming Zhou, Nan Duan:
BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale Pretraining. ICML 2021: 8630-8639 - [c40]Hang Zhang, Yeyun Gong, Yelong Shen, Weisheng Li, Jiancheng Lv, Nan Duan, Weizhu Chen:
Poolingformer: Long Document Modeling with Pooling Attention. ICML 2021: 12437-12446 - [c39]Sandra Sajeev, Jade Huang, Nikos Karampatziakis, Matthew Hall, Sebastian Kochman, Weizhu Chen:
Contextual Bandit Applications in a Customer Support Bot. KDD 2021: 3522-3530 - [c38]Ge Yang, Edward J. Hu, Igor Babuschkin, Szymon Sidor, Xiaodong Liu, David Farhi, Nick Ryder, Jakub Pachocki, Weizhu Chen, Jianfeng Gao:
Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer. NeurIPS 2021: 17084-17097 - [i47]Sewon Min, Jordan L. Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick S. H. Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Sejr Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih:
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. CoRR abs/2101.00133 (2021) - [i46]Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao:
UnitedQA: A Hybrid Approach for Open Domain Question Answering. CoRR abs/2101.00178 (2021) - [i45]Yuning Mao, Pengcheng He, Xiaodong Liu, Yelong Shen, Jianfeng Gao, Jiawei Han, Weizhu Chen:
Reader-Guided Passage Reranking for Open-Domain Question Answering. CoRR abs/2101.00294 (2021) - [i44]Jiachang Liu, Dinghan Shen, Yizhe Zhang, Bill Dolan, Lawrence Carin, Weizhu Chen:
What Makes Good In-Context Examples for GPT-3? CoRR abs/2101.06804 (2021) - [i43]Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Tuo Zhao:
Token-wise Curriculum Learning for Neural Machine Translation. CoRR abs/2103.11088 (2021) - [i42]Jungo Kasai, Hao Peng, Yizhe Zhang, Dani Yogatama, Gabriel Ilharco, Nikolaos Pappas, Yi Mao, Weizhu Chen, Noah A. Smith:
Finetuning Pretrained Transformers into RNNs. CoRR abs/2103.13076 (2021) - [i41]Simiao Zuo, Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach. CoRR abs/2104.04886 (2021) - [i40]Tianyu Liu, Yizhe Zhang, Chris Brockett, Yi Mao, Zhifang Sui, Weizhu Chen, Bill Dolan:
A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation. CoRR abs/2104.08704 (2021) - [i39]Hang Zhang, Yeyun Gong, Yelong Shen, Weisheng Li, Jiancheng Lv, Nan Duan, Weizhu Chen:
Poolingformer: Long Document Modeling with Pooling Attention. CoRR abs/2105.04371 (2021) - [i38]Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen:
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. CoRR abs/2105.12002 (2021) - [i37]Yuekai Zhao, Li Dong, Yelong Shen, Zhihua Zhang, Furu Wei, Weizhu Chen:
Memory-Efficient Differentiable Transformer Architecture Search. CoRR abs/2105.14669 (2021) - [i36]Jiaao Chen, Dinghan Shen, Weizhu Chen, Diyi Yang:
HiddenCut: Simple Data Augmentation for Natural Language Understanding with Better Generalization. CoRR abs/2106.00149 (2021) - [i35]Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Weizhu Chen:
LoRA: Low-Rank Adaptation of Large Language Models. CoRR abs/2106.09685 (2021) - [i34]Simiao Zuo, Chen Liang, Haoming Jiang, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
ARCH: Efficient Adversarial Regularized Training with Caching. CoRR abs/2109.07048 (2021) - [i33]Xiaoze Jiang, Yaobo Liang, Weizhu Chen, Nan Duan:
XLM-K: Improving Cross-Lingual Language Model Pre-Training with Multilingual Knowledge. CoRR abs/2109.12573 (2021) - [i32]Hang Zhang, Yeyun Gong, Yelong Shen, Jiancheng Lv, Nan Duan, Weizhu Chen:
Adversarial Retriever-Ranker for dense text retrieval. CoRR abs/2110.03611 (2021) - [i31]Woojeong Jin, Yu Cheng, Yelong Shen, Weizhu Chen, Xiang Ren:
A Good Prompt Is Worth Millions of Parameters? Low-resource Prompt-based Learning for Vision-Language Models. CoRR abs/2110.08484 (2021) - [i30]Xuxi Chen, Tianlong Chen, Yu Cheng, Weizhu Chen, Zhangyang Wang, Ahmed Hassan Awadallah:
DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models. CoRR abs/2111.00160 (2021) - [i29]Pengcheng He, Jianfeng Gao, Weizhu Chen:
DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing. CoRR abs/2111.09543 (2021) - [i28]Sandra Sajeev, Jade Huang, Nikos Karampatziakis, Matthew Hall, Sebastian Kochman, Weizhu Chen:
Contextual Bandit Applications in Customer Support Bot. CoRR abs/2112.03210 (2021) - 2020
- [c37]Xiaodong Liu, Yu Wang, Jianshu Ji, Hao Cheng, Xueyun Zhu, Emmanuel Awa, Pengcheng He, Weizhu Chen, Hoifung Poon, Guihong Cao, Jianfeng Gao:
The Microsoft Toolkit of Multi-Task Deep Neural Networks for Natural Language Understanding. ACL (demo) 2020: 118-126 - [c36]Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Tuo Zhao:
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization. ACL 2020: 2177-2190 - [c35]Liyuan Liu, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Jiawei Han:
Understanding the Difficulty of Training Transformers. EMNLP (1) 2020: 5747-5763 - [c34]Tao Shen, Yi Mao, Pengcheng He, Guodong Long, Adam Trischler, Weizhu Chen:
Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning. EMNLP (1) 2020: 8980-8994 - [c33]Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han:
On the Variance of the Adaptive Learning Rate and Beyond. ICLR 2020 - [c32]Sewon Min, Jordan L. Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick S. H. Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Sejr Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih:
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. NeurIPS (Competition and Demos) 2020: 86-111 - [i27]Yujia Xie, Tianyi Zhou, Yi Mao, Weizhu Chen:
Conditional Self-Attention for Query-based Summarization. CoRR abs/2002.07338 (2020) - [i26]Xiaodong Liu, Yu Wang, Jianshu Ji, Hao Cheng, Xueyun Zhu, Emmanuel Awa, Pengcheng He, Weizhu Chen, Hoifung Poon, Guihong Cao, Jianfeng Gao:
The Microsoft Toolkit of Multi-Task Deep Neural Networks for Natural Language Understanding. CoRR abs/2002.07972 (2020) - [i25]Liyuan Liu, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Jiawei Han:
Understanding the Difficulty of Training Transformers. CoRR abs/2004.08249 (2020) - [i24]Xiaodong Liu, Hao Cheng, Pengcheng He, Weizhu Chen, Yu Wang, Hoifung Poon, Jianfeng Gao:
Adversarial Training for Large Neural Language Models. CoRR abs/2004.08994 (2020) - [i23]Tao Shen, Yi Mao, Pengcheng He, Guodong Long, Adam Trischler, Weizhu Chen:
Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning. CoRR abs/2004.14224 (2020) - [i22]Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen:
DeBERTa: Decoding-enhanced BERT with Disentangled Attention. CoRR abs/2006.03654 (2020) - [i21]Morteza Ziyadi, Yuting Sun, Abhishek Goswami, Jade Huang, Weizhu Chen:
Example-Based Named Entity Recognition. CoRR abs/2008.10570 (2020) - [i20]Yuning Mao, Pengcheng He, Xiaodong Liu, Yelong Shen, Jianfeng Gao, Jiawei Han, Weizhu Chen:
Generation-Augmented Retrieval for Open-domain Question Answering. CoRR abs/2009.08553 (2020) - [i19]Dinghan Shen, Mingzhi Zheng, Yelong Shen, Yanru Qu, Weizhu Chen:
A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation. CoRR abs/2009.13818 (2020) - [i18]Mingzhi Zheng, Dinghan Shen, Yelong Shen, Weizhu Chen, Lin Xiao:
Improving Self-supervised Pre-training via a Fully-Explored Masked Language Model. CoRR abs/2010.06040 (2020) - [i17]Yanru Qu, Dinghan Shen, Yelong Shen, Sandra Sajeev, Jiawei Han, Weizhu Chen:
CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding. CoRR abs/2010.08670 (2020) - [i16]Kevin J. Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin:
MixKD: Towards Efficient Distillation of Large-scale Language Models. CoRR abs/2011.00593 (2020) - [i15]Dayiheng Liu, Yu Yan, Yeyun Gong, Weizhen Qi, Hang Zhang, Jian Jiao, Weizhu Chen, Jie Fu, Linjun Shou, Ming Gong, Pengcheng Wang, Jiusheng Chen, Daxin Jiang, Jiancheng Lv, Ruofei Zhang, Winnie Wu, Ming Zhou, Nan Duan:
GLGE: A New General Language Generation Evaluation Benchmark. CoRR abs/2011.11928 (2020) - [i14]Jiaxin Huang, Chunyuan Li, Krishan Subudhi, Damien Jose, Shobana Balakrishnan, Weizhu Chen, Baolin Peng, Jianfeng Gao, Jiawei Han:
Few-Shot Named Entity Recognition: A Comprehensive Study. CoRR abs/2012.14978 (2020) - [i13]Weizhen Qi, Yeyun Gong, Jian Jiao, Yu Yan, Dayiheng Liu, Weizhu Chen, Kewen Tang, Houqiang Li, Jiusheng Chen, Ruofei Zhang, Ming Zhou, Nan Duan:
BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale Pretraining. CoRR abs/2012.15525 (2020)
2010 – 2019
- 2019
- [j1]Lin Xiao, Adams Wei Yu, Qihang Lin, Weizhu Chen:
DSCOVR: Randomized Primal-Dual Block Coordinate Algorithms for Asynchronous Distributed Optimization. J. Mach. Learn. Res. 20: 43:1-43:58 (2019) - [c31]Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao:
Multi-Task Deep Neural Networks for Natural Language Understanding. ACL (1) 2019: 4487-4496 - [c30]Ziyi Yang, Chenguang Zhu, Weizhu Chen:
Parameter-free Sentence Embedding via Orthogonal Basis. EMNLP/IJCNLP (1) 2019: 638-648 - [c29]Jianmo Ni, Chenguang Zhu, Weizhu Chen, Julian J. McAuley:
Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Open-domain Question Answering. NAACL-HLT (1) 2019: 335-344 - [i12]Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao:
Multi-Task Deep Neural Networks for Natural Language Understanding. CoRR abs/1901.11504 (2019) - [i11]Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao:
Improving Multi-Task Deep Neural Networks via Knowledge Distillation for Natural Language Understanding. CoRR abs/1904.09482 (2019) - [i10]Nikos Karampatziakis, Sebastian Kochman, Jade Huang, Paul Mineiro, Kathy Osborne, Weizhu Chen:
Lessons from Real-World Reinforcement Learning in a Customer Support Bot. CoRR abs/1905.02219 (2019) - [i9]Pengcheng He, Xiaodong Liu, Weizhu Chen, Jianfeng Gao:
A Hybrid Neural Network Model for Commonsense Reasoning. CoRR abs/1907.11983 (2019) - [i8]Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han:
On the Variance of the Adaptive Learning Rate and Beyond. CoRR abs/1908.03265 (2019) - [i7]Pengcheng He, Yi Mao, Kaushik Chakrabarti, Weizhu Chen:
X-SQL: reinforce schema representation with context. CoRR abs/1908.08113 (2019) - [i6]Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Tuo Zhao:
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization. CoRR abs/1911.03437 (2019) - 2018
- [c28]Hsin-Yuan Huang, Chenguang Zhu, Yelong Shen, Weizhu Chen:
FusionNet: Fusing via Fully-aware Attention with Application to Machine Comprehension. ICLR (Poster) 2018 - [i5]Jianmo Ni, Chenguang Zhu, Weizhu Chen, Julian J. McAuley:
Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Scientific Question Answering. CoRR abs/1808.09492 (2018) - [i4]Tianze Shi, Kedar Tatwawadi, Kaushik Chakrabarti, Yi Mao, Oleksandr Polozov, Weizhu Chen:
IncSQL: Training Incremental Text-to-SQL Parsers with Non-Deterministic Oracles. CoRR abs/1809.05054 (2018) - [i3]Ziyi Yang, Chenguang Zhu, Weizhu Chen:
Zero-training Sentence Embedding via Orthogonal Basis. CoRR abs/1810.00438 (2018) - 2017
- [c27]Yelong Shen, Po-Sen Huang, Jianfeng Gao, Weizhu Chen:
ReasoNet: Learning to Stop Reading in Machine Comprehension. KDD 2017: 1047-1055 - [c26]Ching-Pei Lee, Po-Wei Wang, Weizhu Chen, Chih-Jen Lin:
Limited-memory Common-directions Method for Distributed Optimization and its Application on Empirical Risk Minimization. SDM 2017: 732-740 - [i2]Hsin-Yuan Huang, Chenguang Zhu, Yelong Shen, Weizhu Chen:
FusionNet: Fusing via Fully-Aware Attention with Application to Machine Comprehension. CoRR abs/1711.07341 (2017) - 2016
- [c25]Yelong Shen, Po-Sen Huang, Jianfeng Gao, Weizhu Chen:
ReasoNet: Learning to Stop Reading in Machine Comprehension. CoCo@NIPS 2016 - [i1]Yelong Shen, Po-Sen Huang, Jianfeng Gao, Weizhu Chen:
ReasoNet: Learning to Stop Reading in Machine Comprehension. CoRR abs/1609.05284 (2016) - 2014
- [c24]Yangqiu Song, Haixun Wang, Weizhu Chen, Shusen Wang:
Transfer Understanding from Head Queries to Tail Queries. CIKM 2014: 1299-1308 - [c23]Weizhu Chen, Zhenghao Wang, Jingren Zhou:
Large-scale L-BFGS using MapReduce. NIPS 2014: 1332-1340 - 2012
- [c22]Weizhu Chen, Dong Wang, Yuchen Zhang, Zheng Chen, Adish Singla, Qiang Yang:
A noise-aware click model for web search. WSDM 2012: 313-322 - [c21]Si Shen, Botao Hu, Weizhu Chen, Qiang Yang:
Personalized click model through collaborative filtering. WSDM 2012: 323-332 - [c20]Danqi Chen, Weizhu Chen, Haixun Wang, Zheng Chen, Qiang Yang:
Beyond ten blue links: enabling user click modeling in federated web search. WSDM 2012: 463-472 - 2011
- [c19]Weizhu Chen, Zhanglong Ji, Si Shen, Qiang Yang:
A Whole Page Click Model to Better Interpret Search Engine Click Data. AAAI 2011 - [c18]Danqi Chen, Weizhu Chen, Qiang Yang:
Characterizing Inverse Time Dependency in Multi-class Learning. ICDM 2011: 1020-1025 - [c17]Yangqiu Song, Haixun Wang, Zhongyuan Wang, Hongsong Li, Weizhu Chen:
Short Text Conceptualization Using a Probabilistic Knowledgebase. IJCAI 2011: 2330-2336 - [c16]Yuchen Zhang, Weizhu Chen, Dong Wang, Qiang Yang:
User-click modeling for understanding and predicting search-behavior. KDD 2011: 1388-1396 - [c15]Dakan Wang, Gang Wang, Xiaofeng Ke, Weizhu Chen:
Action prediction and identification from mining temporal user behaviors. WSDM 2011: 435-444 - [c14]Botao Hu, Yuchen Zhang, Weizhu Chen, Gang Wang, Qiang Yang:
Characterizing search intent diversity into click models. WWW 2011: 17-26 - 2010
- [c13]Yuchen Zhang, Dong Wang, Gang Wang, Weizhu Chen, Zhihua Zhang, Botao Hu, Li Zhang:
Learning click models via probit bayesian inference. CIKM 2010: 439-448 - [c12]Dong Wang, Weizhu Chen, Gang Wang, Yuchen Zhang, Botao Hu:
Explore click models for search ranking. CIKM 2010: 1417-1420 - [c11]Feimin Zhong, Dong Wang, Gang Wang, Weizhu Chen, Yuchen Zhang, Zheng Chen, Haixun Wang:
Incorporating post-click behaviors into a click model. SIGIR 2010: 355-362 - [c10]Zeyuan Allen Zhu, Weizhu Chen, Tom Minka, Chenguang Zhu, Zheng Chen:
A novel click model and its applications to online advertising. WSDM 2010: 321-330 - [c9]Dong Wang, Chenguang Zhu, Weizhu Chen, Gang Wang, Zheng Chen:
Co-optimization of multiple relevance metrics in web search. WWW 2010: 1199-1200
2000 – 2009
- 2009
- [c8]