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Xiaodong Liu 0003
Person information
- affiliation: Microsoft Research, Redmond, WA, USA
- affiliation (PhD 2015): Nara Institute of Science and Technology, Takayama, Japan
- affiliation (former): Beijing University of Posts and Telecommunications, Center for Intelligence Science and Technology, Beijing, China
- affiliation (former): University of Tokushima, Department of Information Sciences and Intelligent Systems, Tokushima, Japan
Other persons with the same name
- Xiaodong Liu (aka: Xiao-Dong Liu) — disambiguation page
- Xiaodong Liu 0001
— Dalian University of Technology, Faculty of Electronic Information and Electrical Engineering, Research Center of Information and Control, Dalian, China (and 2 more)
- Xiaodong Liu 0002
— Edinburgh Napier University, School of Computing, Edinburgh, UK (and 1 more)
- Xiaodong Liu 0004
— National University of Defense Technology, School of Computer, Changsha, China
- Xiaodong Liu 0005 — Tsinghua University, Graduate School at Shenzhen, Broadband Network and Multimedia Research Center, Shenzhen, China
- Xiaodong Liu 0006
— Wuhan University, School of Electronic Information, Wuhan, China (and 1 more)
- Xiaodong Liu 0007 — Xi'an University of Finance and Economics, School of Management Engineering, Xi'an, China (and 1 more)
- Xiaodong Liu 0008
— National University of Singapore, Department of Electrical and Computer Engineering, Singapore
- Xiaodong Liu 0009
— Remcom Inc., State College, PA, USA (and 2 more)
- Xiaodong Liu 0010
— Beijing University of Technology, Faculty of Information Technology, Beijing, China
- Xiaodong Liu 0011
— Beijing Aerospace Automatic Control Institute, China (and 1 more)
- Xiaodong Liu 0012
— Qingdao University, Department of Management Science and Engineering, Qingdao, China
- Xiaodong Liu 0013
— Henan University of Engineering, School of Computing, Zhengzhou, China (and 1 more)
- Xiaodong Liu 0014
— Jinan University, College of Information Science and Technology and the College of Cyber Security, Guangzhou, China
- Xiaodong Liu 0015
(aka: Xiao-Dong Liu 0015) — Jiangsu University, Synergistic Innovation Center of Jiangsu Modern Agricultural Equipment and Technology, Zhenjiang, China (and 1 more)
- Xiaodong Liu 0016
— TUMCREATE Ltd, Singapore
- Xiaodong Liu 0017 — Fudan University, School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing, Shanghai, China (and 1 more)
- Xiaodong Liu 0018 — Fudan University, Microelectronics Department, State Key Laboratory of ASIC and System, Shanghai, China (and 1 more)
- Xiaodong Liu 0019 — Northwestern Polytechnical University, School of Electronics and Information, Xi'an, China
- Xiaodong Liu 0020
— Chinese Academy of Sciences, Academy of Mathematics and Systems Science, Institute of Applied Mathematics, Beijing, China
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2020 – today
- 2024
- [c59]Zonglin Yang, Li Dong, Xinya Du, Hao Cheng, Erik Cambria, Xiaodong Liu, Jianfeng Gao, Furu Wei:
Language Models as Inductive Reasoners. EACL (1) 2024: 209-225 - [c58]Chengyu Dong, Liyuan Liu, Hao Cheng, Jingbo Shang, Jianfeng Gao, Xiaodong Liu:
Fast-ELECTRA for Efficient Pre-training. ICLR 2024 - [c57]Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao:
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. ICLR 2024 - [i69]Yanda Chen, Chandan Singh, Xiaodong Liu, Simiao Zuo, Bin Yu, He He, Jianfeng Gao:
Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning. CoRR abs/2401.13986 (2024) - 2023
- [j4]Robert Tinn, Hao Cheng, Yu Gu, Naoto Usuyama, Xiaodong Liu, Tristan Naumann
, Jianfeng Gao, Hoifung Poon
:
Fine-tuning large neural language models for biomedical natural language processing. Patterns 4(4): 100729 (2023) - [c56]Hao Cheng, Hao Fang, Xiaodong Liu, Jianfeng Gao:
Task-Aware Specialization for Efficient and Robust Dense Retrieval for Open-Domain Question Answering. ACL (2) 2023: 1864-1875 - [c55]Ganesh Jawahar, Subhabrata Mukherjee, Xiaodong Liu, Young Jin Kim, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah, Sébastien Bubeck, Jianfeng Gao:
AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine Translation. ACL (Findings) 2023: 9116-9132 - [c54]Yu Zhang, Hao Cheng, Zhihong Shen, Xiaodong Liu, Ye-Yi Wang, Jianfeng Gao:
Pre-training Multi-task Contrastive Learning Models for Scientific Literature Understanding. EMNLP (Findings) 2023: 12259-12275 - [c53]Weizhi Wang, Li Dong, Hao Cheng, Haoyu Song, Xiaodong Liu, Xifeng Yan
, Jianfeng Gao, Furu Wei:
Visually-Augmented Language Modeling. ICLR 2023 - [c52]Chengyu Dong, Liyuan Liu, Hao Cheng, Jingbo Shang, Jianfeng Gao, Xiaodong Liu:
Understand and Modularize Generator Optimization in ELECTRA-style Pretraining. ICML 2023: 8244-8259 - [c51]Liyuan Liu, Chengyu Dong, Xiaodong Liu, Bin Yu, Jianfeng Gao:
Bridging Discrete and Backpropagation: Straight-Through and Beyond. NeurIPS 2023 - [c50]Weizhi Wang, Li Dong, Hao Cheng, Xiaodong Liu, Xifeng Yan, Jianfeng Gao, Furu Wei:
Augmenting Language Models with Long-Term Memory. NeurIPS 2023 - [i68]Sanxing Chen, Hao Cheng, Xiaodong Liu, Jian Jiao, Yangfeng Ji, Jianfeng Gao:
Pre-training Transformers for Knowledge Graph Completion. CoRR abs/2303.15682 (2023) - [i67]Liyuan Liu, Chengyu Dong, Xiaodong Liu, Bin Yu, Jianfeng Gao:
Bridging Discrete and Backpropagation: Straight-Through and Beyond. CoRR abs/2304.08612 (2023) - [i66]Kaixin Ma, Hao Cheng, Yu Zhang, Xiaodong Liu, Eric Nyberg, Jianfeng Gao:
Chain-of-Skills: A Configurable Model for Open-domain Question Answering. CoRR abs/2305.03130 (2023) - [i65]Yu Zhang, Hao Cheng, Zhihong Shen, Xiaodong Liu, Ye-Yi Wang, Jianfeng Gao:
Pre-training Multi-task Contrastive Learning Models for Scientific Literature Understanding. CoRR abs/2305.14232 (2023) - [i64]Weizhi Wang, Li Dong, Hao Cheng, Xiaodong Liu, Xifeng Yan, Jianfeng Gao, Furu Wei:
Augmenting Language Models with Long-Term Memory. CoRR abs/2306.07174 (2023) - [i63]Chengyu Dong, Liyuan Liu, Hao Cheng, Jingbo Shang, Jianfeng Gao, Xiaodong Liu:
Fast-ELECTRA for Efficient Pre-training. CoRR abs/2310.07347 (2023) - [i62]Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao:
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. CoRR abs/2311.02262 (2023) - 2022
- [j3]Yu Gu
, Robert Tinn, Hao Cheng, Michael Lucas, Naoto Usuyama, Xiaodong Liu, Tristan Naumann
, Jianfeng Gao, Hoifung Poon:
Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing. ACM Trans. Comput. Heal. 3(1): 2:1-2:23 (2022) - [c49]Kaixin Ma, Hao Cheng, Xiaodong Liu, Eric Nyberg, Jianfeng Gao:
Open Domain Question Answering with A Unified Knowledge Interface. ACL (1) 2022: 1605-1620 - [c48]Sheng Zhang, Hao Cheng, Shikhar Vashishth, Cliff Wong, Jinfeng Xiao, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon:
Knowledge-Rich Self-Supervision for Biomedical Entity Linking. EMNLP (Findings) 2022: 868-880 - [c47]Kaixin Ma, Hao Cheng, Xiaodong Liu, Eric Nyberg, Jianfeng Gao:
Open-domain Question Answering via Chain of Reasoning over Heterogeneous Knowledge. EMNLP (Findings) 2022: 5360-5374 - [c46]Yaqing Wang, Sahaj Agarwal, Subhabrata Mukherjee, Xiaodong Liu, Jing Gao, Ahmed Hassan Awadallah, Jianfeng Gao:
AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning. EMNLP 2022: 5744-5760 - [c45]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. ICLR 2022 - [c44]Simiao Zuo, Xiaodong Liu, Jian Jiao, Young Jin Kim, Hany Hassan, Ruofei Zhang, Jianfeng Gao, Tuo Zhao:
Taming Sparsely Activated Transformer with Stochastic Experts. ICLR 2022 - [c43]Yichong Xu, Chenguang Zhu, Shuohang Wang, Siqi Sun, Hao Cheng, Xiaodong Liu, Jianfeng Gao, Pengcheng He, Michael Zeng, Xuedong Huang:
Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention. IJCAI 2022: 2762-2768 - [c42]Yaqing Wang, Subhabrata Mukherjee, Xiaodong Liu, Jing Gao, Ahmed Awadallah, Jianfeng Gao:
LiST: Lite Prompted Self-training Makes Parameter-efficient Few-shot Learners. NAACL-HLT (Findings) 2022: 2262-2281 - [c41]Dongkuan Xu, Subhabrata Mukherjee, Xiaodong Liu, Debadeepta Dey, Wenhui Wang, Xiang Zhang, Ahmed Hassan Awadallah, Jianfeng Gao:
Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models. NeurIPS 2022 - [i61]Dongkuan Xu, Subhabrata Mukherjee, Xiaodong Liu, Debadeepta Dey, Wenhui Wang, Xiang Zhang, Ahmed Hassan Awadallah, Jianfeng Gao:
AutoDistil: Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models. CoRR abs/2201.12507 (2022) - [i60]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) - [i59]Da Yin, Li Dong, Hao Cheng, Xiaodong Liu, Kai-Wei Chang, Furu Wei, Jianfeng Gao:
A Survey of Knowledge-Intensive NLP with Pre-Trained Language Models. CoRR abs/2202.08772 (2022) - [i58]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) - [i57]Payal Bajaj, Chenyan Xiong, Guolin Ke, Xiaodong Liu, Di He, Saurabh Tiwary, Tie-Yan Liu, Paul Bennett, Xia Song, Jianfeng Gao:
METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals. CoRR abs/2204.06644 (2022) - [i56]Weizhi Wang, Li Dong, Hao Cheng, Haoyu Song, Xiaodong Liu, Xifeng Yan, Jianfeng Gao, Furu Wei:
Visually-Augmented Language Modeling. CoRR abs/2205.10178 (2022) - [i55]Yaqing Wang, Subhabrata Mukherjee, Xiaodong Liu, Jing Gao, Ahmed Hassan Awadallah, Jianfeng Gao:
AdaMix: Mixture-of-Adapter for Parameter-efficient Tuning of Large Language Models. CoRR abs/2205.12410 (2022) - [i54]Hao Cheng, Hao Fang, Xiaodong Liu, Jianfeng Gao:
Task-Aware Specialization for Efficient and Robust Dense Retrieval for Open-Domain Question Answering. CoRR abs/2210.05156 (2022) - [i53]Ganesh Jawahar, Subhabrata Mukherjee, Xiaodong Liu, Young Jin Kim
, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah, Sébastien Bubeck, Jianfeng Gao:
AutoMoE: Neural Architecture Search for Efficient Sparsely Activated Transformers. CoRR abs/2210.07535 (2022) - [i52]Kaixin Ma, Hao Cheng, Xiaodong Liu, Eric Nyberg, Jianfeng Gao:
Open-domain Question Answering via Chain of Reasoning over Heterogeneous Knowledge. CoRR abs/2210.12338 (2022) - [i51]Simiao Zuo, Xiaodong Liu, Jian Jiao, Denis Charles, Eren Manavoglu, Tuo Zhao, Jianfeng Gao:
Efficient Long Sequence Modeling via State Space Augmented Transformer. CoRR abs/2212.08136 (2022) - [i50]Zonglin Yang
, Li Dong, Xinya Du, Hao Cheng, Erik Cambria, Xiaodong Liu, Jianfeng Gao, Furu Wei:
Language Models as Inductive Reasoners. CoRR abs/2212.10923 (2022) - 2021
- [c40]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 - [c39]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 - [c38]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 - [c37]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 - [c36]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 - [c35]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 - [c34]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 - [c33]Sanxing Chen, Xiaodong Liu, Jianfeng Gao, Jian Jiao, Ruofei Zhang, Yangfeng Ji:
HittER: Hierarchical Transformers for Knowledge Graph Embeddings. EMNLP (1) 2021: 10395-10407 - [c32]Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen:
Deberta: decoding-Enhanced Bert with Disentangled Attention. ICLR 2021 - [c31]Hao Cheng, Xiaodong Liu, Lis Pereira, Yaoliang Yu, Jianfeng Gao:
Posterior Differential Regularization with f-divergence for Improving Model Robustness. NAACL-HLT 2021: 1078-1089 - [c30]Lis Pereira, Xiaodong Liu, Hao Cheng, Hoifung Poon, Jianfeng Gao, Ichiro Kobayashi:
Targeted Adversarial Training for Natural Language Understanding. NAACL-HLT 2021: 5385-5393 - [c29]Subhabrata Mukherjee, Xiaodong Liu, Guoqing Zheng, Saghar Hosseini, Hao Cheng, Ge Yang, Christopher Meek, Ahmed Hassan Awadallah, Jianfeng Gao:
Few-Shot Learning Evaluation in Natural Language Understanding. NeurIPS Datasets and Benchmarks 2021 - [c28]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 - [i49]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) - [i48]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) - [i47]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) - [i46]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) - [i45]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) - [i44]Lis Pereira, Xiaodong Liu, Hao Cheng, Hoifung Poon, Jianfeng Gao, Ichiro Kobayashi:
Targeted Adversarial Training for Natural Language Understanding. CoRR abs/2104.05847 (2021) - [i43]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) - [i42]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) - [i41]Simiao Zuo, Xiaodong Liu, Jian Jiao, Young Jin Kim, Hany Hassan, Ruofei Zhang, Tuo Zhao, Jianfeng Gao:
Taming Sparsely Activated Transformer with Stochastic Experts. CoRR abs/2110.04260 (2021) - [i40]Yaqing Wang, Subhabrata Mukherjee, Xiaodong Liu, Jing Gao, Ahmed Hassan Awadallah, Jianfeng Gao:
LiST: Lite Self-training Makes Efficient Few-shot Learners. CoRR abs/2110.06274 (2021) - [i39]Kaixin Ma, Hao Cheng, Xiaodong Liu, Eric Nyberg, Jianfeng Gao:
Open Domain Question Answering over Virtual Documents: A Unified Approach for Data and Text. CoRR abs/2110.08417 (2021) - [i38]Subhabrata Mukherjee, Xiaodong Liu, Guoqing Zheng, Saghar Hosseini, Hao Cheng, Greg Yang, Christopher Meek, Ahmed Hassan Awadallah, Jianfeng Gao:
CLUES: Few-Shot Learning Evaluation in Natural Language Understanding. CoRR abs/2111.02570 (2021) - [i37]Yichong Xu, Chenguang Zhu, Shuohang Wang, Siqi Sun, Hao Cheng, Xiaodong Liu, Jianfeng Gao, Pengcheng He, Michael Zeng, Xuedong Huang:
Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention. CoRR abs/2112.03254 (2021) - [i36]Robert Tinn, Hao Cheng, Yu Gu, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon:
Fine-Tuning Large Neural Language Models for Biomedical Natural Language Processing. CoRR abs/2112.07869 (2021) - [i35]Sheng Zhang, Hao Cheng, Shikhar Vashishth, Cliff Wong, Jinfeng Xiao, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon:
Knowledge-Rich Self-Supervised Entity Linking. CoRR abs/2112.07887 (2021) - 2020
- [c27]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 - [c26]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 - [c25]Bailin Wang, Richard Shin, Xiaodong Liu, Oleksandr Polozov, Matthew Richardson:
RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers. ACL 2020: 7567-7578 - [c24]Sanxing Chen, Aidan San, Xiaodong Liu, Yangfeng Ji:
A Tale of Two Linkings: Dynamically Gating between Schema Linking and Structural Linking for Text-to-SQL Parsing. COLING 2020: 2900-2912 - [c23]Liyuan Liu, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Jiawei Han:
Understanding the Difficulty of Training Transformers. EMNLP (1) 2020: 5747-5763 - [c22]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 - [c21]Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Xiaodong Liu, Yu Wang, Jianfeng Gao, Songhao Piao, Ming Zhou, Hsiao-Wuen Hon:
UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training. ICML 2020: 642-652 - [c20]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 - [c19]Lis Pereira, Xiaodong Liu
, Fei Cheng, Masayuki Asahara, Ichiro Kobayashi:
Adversarial Training for Commonsense Inference. RepL4NLP@ACL 2020: 55-60 - [i34]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) - [i33]Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Xiaodong Liu, Yu Wang, Songhao Piao, Jianfeng Gao, Ming Zhou, Hsiao-Wuen Hon:
UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training. CoRR abs/2002.12804 (2020) - [i32]Liyuan Liu, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Jiawei Han:
Understanding the Difficulty of Training Transformers. CoRR abs/2004.08249 (2020) - [i31]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) - [i30]Lis Pereira, Xiaodong Liu, Fei Cheng, Masayuki Asahara, Ichiro Kobayashi:
Adversarial Training for Commonsense Inference. CoRR abs/2005.08156 (2020) - [i29]Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen:
DeBERTa: Decoding-enhanced BERT with Disentangled Attention. CoRR abs/2006.03654 (2020) - [i28]Yu Gu, Robert Tinn, Hao Cheng, Michael Lucas, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon:
Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing. CoRR abs/2007.15779 (2020) - [i27]Xiaodong Liu, Kevin Duh, Liyuan Liu, Jianfeng Gao:
Very Deep Transformers for Neural Machine Translation. CoRR abs/2008.07772 (2020) - [i26]Sanxing Chen
, Xiaodong Liu, Jianfeng Gao, Jian Jiao, Ruofei Zhang, Yangfeng Ji:
HittER: Hierarchical Transformers for Knowledge Graph Embeddings. CoRR abs/2008.12813 (2020) - [i25]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) - [i24]Sanxing Chen, Aidan San, Xiaodong Liu, Yangfeng Ji:
A Tale of Two Linkings: Dynamically Gating between Schema Linking and Structural Linking for Text-to-SQL Parsing. CoRR abs/2009.14809 (2020) - [i23]Hao Cheng, Xiaodong Liu, Lis Pereira, Yaoliang Yu, Jianfeng Gao:
Posterior Differential Regularization with f-divergence for Improving Model Robustness. CoRR abs/2010.12638 (2020)
2010 – 2019
- 2019
- [c18]Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao:
Multi-Task Deep Neural Networks for Natural Language Understanding. ACL (1) 2019: 4487-4496 - [c17]Lianhui Qin, Michel Galley, Chris Brockett, Xiaodong Liu, Xiang Gao, Bill Dolan, Yejin Choi, Jianfeng Gao:
Conversing by Reading: Contentful Neural Conversation with On-demand Machine Reading. ACL (1) 2019: 5427-5436 - [c16]Yichong Xu, Xiaodong Liu, Chunyuan Li, Hoifung Poon, Jianfeng Gao:
DoubleTransfer at MEDIQA 2019: Multi-Source Transfer Learning for Natural Language Understanding in the Medical Domain. BioNLP@ACL 2019: 399-405 - [c15]Liu Yang, Junjie Hu, Minghui Qiu, Chen Qu, Jianfeng Gao, W. Bruce Croft, Xiaodong Liu, Yelong Shen, Jingjing Liu:
A Hybrid Retrieval-Generation Neural Conversation Model. CIKM 2019: 1341-1350 - [c14]Huazheng Wang, Zhe Gan, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Hongning Wang:
Adversarial Domain Adaptation for Machine Reading Comprehension. EMNLP/IJCNLP (1) 2019: 2510-2520 - [c13]Hao Fu, Chunyuan Li, Xiaodong Liu, Jianfeng Gao, Asli Celikyilmaz, Lawrence Carin:
Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing. NAACL-HLT (1) 2019: 240-250 - [c12]Shuohang Wang, Sheng Zhang, Yelong Shen, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Jing Jiang
:
Unsupervised Deep Structured Semantic Models for Commonsense Reasoning. NAACL-HLT (1) 2019: 882-891 - [c11]Yichong Xu, Xiaodong Liu, Yelong Shen, Jingjing Liu, Jianfeng Gao:
Multi-task Learning with Sample Re-weighting for Machine Reading Comprehension. NAACL-HLT (1) 2019: 2644-2655 - [c10]Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, Hsiao-Wuen Hon:
Unified Language Model Pre-training for Natural Language Understanding and Generation. NeurIPS 2019: 13042-13054 - [i22]Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao:
Multi-Task Deep Neural Networks for Natural Language Understanding. CoRR abs/1901.11504 (2019) - [i21]Hao Fu, Chunyuan Li, Xiaodong Liu, Jianfeng Gao, Asli Celikyilmaz, Lawrence Carin:
Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing. CoRR abs/1903.10145 (2019) - [i20]Shuohang Wang, Sheng Zhang, Yelong Shen, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Jing Jiang:
Unsupervised Deep Structured Semantic Models for Commonsense Reasoning. CoRR abs/1904.01938 (2019) - [i19]Liu Yang, Junjie Hu, Minghui Qiu, Chen Qu, Jianfeng Gao, W. Bruce Croft, Xiaodong Liu, Yelong Shen, Jingjing Liu:
A Hybrid Retrieval-Generation Neural Conversation Model. CoRR abs/1904.09068 (2019) - [i18]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) - [i17]Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, Hsiao-Wuen Hon:
Unified Language Model Pre-training for Natural Language Understanding and Generation. CoRR abs/1905.03197 (2019) - [i16]Lianhui Qin, Michel Galley, Chris Brockett, Xiaodong Liu, Xiang Gao, Bill Dolan, Yejin Choi, Jianfeng Gao:
Conversing by Reading: Contentful Neural Conversation with On-demand Machine Reading. CoRR abs/1906.02738 (2019) - [i15]Yichong Xu, Xiaodong Liu, Chunyuan Li, Hoifung Poon, Jianfeng Gao:
DoubleTransfer at MEDIQA 2019: Multi-Source Transfer Learning for Natural Language Understanding in the Medical Domain. CoRR abs/1906.04382 (2019) - [i14]Pengcheng He, Xiaodong Liu, Weizhu Chen, Jianfeng Gao:
A Hybrid Neural Network Model for Commonsense Reasoning. CoRR abs/1907.11983 (2019) - [i13]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) - [i12]Huazheng Wang, Zhe Gan, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Hongning Wang:
Adversarial Domain Adaptation for Machine Reading Comprehension. CoRR abs/1908.09209 (2019) - [i11]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) - [i10]Bailin Wang, Richard Shin, Xiaodong Liu, Oleksandr Polozov, Matthew Richardson:
RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers. CoRR abs/1911.04942 (2019) - 2018
- [c9]Xiaodong Liu, Yelong Shen, Kevin Duh, Jianfeng Gao:
Stochastic Answer Networks for Machine Reading Comprehension. ACL (1) 2018: 1694-1704 - [c8]Jianbo Chen, Yelong Shen, Jianfeng Gao, Jingjing Liu, Xiaodong Liu:
Language-Based Image Editing With Recurrent Attentive Models. CVPR 2018: 8721-8729 - [c7]Minjia Zhang, Wenhan Wang, Xiaodong Liu, Jianfeng Gao, Yuxiong He:
Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models. NeurIPS 2018: 6311-6322 - [i9]Xiaodong Liu, Kevin Duh, Jianfeng Gao:
Stochastic Answer Networks for Natural Language Inference. CoRR abs/1804.07888 (2018) - [i8]Minjia Zhang, Xiaodong Liu, Wenhan Wang, Jianfeng Gao, Yuxiong He:
Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models. CoRR abs/1806.04189 (2018) - [i7]Yichong Xu, Xiaodong Liu, Yelong Shen, Jingjing Liu, Jianfeng Gao:
Multi-Task Learning for Machine Reading Comprehension. CoRR abs/1809.06963 (2018) - [i6]Xiaodong Liu, Wei Li, Yuwei Fang, Aerin Kim, Kevin Duh, Jianfeng Gao:
Stochastic Answer Networks for SQuAD 2.0. CoRR abs/1809.09194 (2018) - [i5]Sheng Zhang, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Kevin Duh, Benjamin Van Durme:
ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension. CoRR abs/1810.12885 (2018) - 2017
- [c6]Lis Pereira, Xiaodong Liu, John Lee:
Lexical Simplification with the Deep Structured Similarity Model. IJCNLP(2) 2017: 430-435 - [c5]Yelong Shen, Xiaodong Liu, Kevin Duh, Jianfeng Gao:
An Empirical Analysis of Multiple-Turn Reasoning Strategies in Reading Comprehension Tasks. IJCNLP(1) 2017: 957-966 - [i4]Yelong Shen, Xiaodong Liu, Kevin Duh, Jianfeng Gao:
An Empirical Analysis of Multiple-Turn Reasoning Strategies in Reading Comprehension Tasks. CoRR abs/1711.03230 (2017) - [i3]Yichong Xu, Jingjing Liu, Jianfeng Gao, Yelong Shen, Xiaodong Liu:
Towards Human-level Machine Reading Comprehension: Reasoning and Inference with Multiple Strategies. CoRR abs/1711.04964 (2017) - [i2]Jianbo Chen, Yelong Shen, Jianfeng Gao, Jingjing Liu, Xiaodong Liu:
Language-Based Image Editing with Recurrent Attentive Models. CoRR abs/1711.06288 (2017) - [i1]Xiaodong Liu, Yelong Shen, Kevin Duh, Jianfeng Gao:
Stochastic Answer Networks for Machine Reading Comprehension. CoRR abs/1712.03556 (2017) - 2015
- [j2]Xiaodong Liu, Kevin Duh, Yuji Matsumoto:
Multilingual Topic Models for Bilingual Dictionary Extraction. ACM Trans. Asian Low Resour. Lang. Inf. Process. 14(3): 11:1-11:22 (2015) - [j1]Xiaodong Liu, Fei Cheng, Kevin Duh, Yuji Matsumoto:
A Hybrid Ranking Approach to Chinese Spelling Check. ACM Trans. Asian Low Resour. Lang. Inf. Process. 14(4): 16:1-16:17 (2015) - [c4]Xiaodong Liu, Jianfeng Gao, Xiaodong He, Li Deng, Kevin Duh, Ye-Yi Wang:
Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval. HLT-NAACL 2015: 912-921 - 2013
- [c3]Xiaodong Liu, Kevin Cheng, Yanyan Luo, Kevin Duh, Yuji Matsumoto:
A Hybrid Chinese Spelling Correction Using Language Model and Statistical Machine Translation with Reranking. SIGHAN@IJCNLP 2013: 54-58 - [c2]Xiaodong Liu, Kevin Duh, Yuji Matsumoto:
Topic Models + Word Alignment = A Flexible Framework for Extracting Bilingual Dictionary from Comparable Corpus. CoNLL 2013: 212-221 - 2010
- [c1]Xiaodong Liu, Fuji Ren, Caixia Yuan:
Use relative weight to improve the kNN for unbalanced text category. NLPKE 2010: 1-5
Coauthor Index
aka: Ahmed Hassan Awadallah
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