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2020 – today
- 2022
[c21]Qintong Li, Piji Li, Wei Bi, Zhaochun Ren, Yuxuan Lai, Lingpeng Kong:
Event Transition Planning for Open-ended Text Generation. ACL (Findings) 2022: 3412-3426- [c20]Hao Peng, Jungo Kasai, Nikolaos Pappas, Dani Yogatama, Zhaofeng Wu, Lingpeng Kong, Roy Schwartz, Noah A. Smith:
ABC: Attention with Bounded-memory Control. ACL (1) 2022: 7469-7483 - [c19]Zhiyong Wu, Wei Bi, Xiang Li, Lingpeng Kong, Ben Kao:
Lexical Knowledge Internalization for Neural Dialog Generation. ACL (1) 2022: 7945-7958 - [i35]Tianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong, Torsten Scholak, Michihiro Yasunaga, Chien-Sheng Wu, Ming Zhong, Pengcheng Yin, Sida I. Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir R. Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A. Smith, Luke Zettlemoyer, Tao Yu:
UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models. CoRR abs/2201.05966 (2022) - [i34]Hao Wang, Yangguang Li, Zhen Huang, Yong Dou, Lingpeng Kong, Jing Shao:
SNCSE: Contrastive Learning for Unsupervised Sentence Embedding with Soft Negative Samples. CoRR abs/2201.05979 (2022) - [i33]Yixuan Su, Tian Lan, Yan Wang, Dani Yogatama, Lingpeng Kong, Nigel Collier:
A Contrastive Framework for Neural Text Generation. CoRR abs/2202.06417 (2022) - [i32]Jiacheng Ye, Jiahui Gao, Qintong Li, Hang Xu, Jiangtao Feng, Zhiyong Wu, Tao Yu, Lingpeng Kong:
ZeroGen: Efficient Zero-shot Learning via Dataset Generation. CoRR abs/2202.07922 (2022) - [i31]Han Shi, Jiahui Gao, Hang Xu, Xiaodan Liang, Zhenguo Li, Lingpeng Kong, Stephen M. S. Lee, James T. Kwok:
Revisiting Over-smoothing in BERT from the Perspective of Graph. CoRR abs/2202.08625 (2022) - [i30]Zhen Qin, Weixuan Sun, Hui Deng, Dongxu Li, Yunshen Wei, Baohong Lv, Junjie Yan, Lingpeng Kong, Yiran Zhong:
cosFormer: Rethinking Softmax in Attention. CoRR abs/2202.08791 (2022) - [i29]Lin Zheng, Chong Wang, Lingpeng Kong:
Linear Complexity Randomized Self-attention Mechanism. CoRR abs/2204.04667 (2022) - [i28]Qintong Li, Piji Li, Wei Bi, Zhaochun Ren, Yuxuan Lai, Lingpeng Kong:
Event Transition Planning for Open-ended Text Generation. CoRR abs/2204.09453 (2022) - [i27]Zhiyong Wu, Wei Bi, Xiang Li, Lingpeng Kong, Ben Kao:
Lexical Knowledge Internalization for Neural Dialog Generation. CoRR abs/2205.01941 (2022) - [i26]Yixuan Su, Tian Lan, Yahui Liu, Fangyu Liu, Dani Yogatama, Yan Wang, Lingpeng Kong, Nigel Collier:
Language Models Can See: Plugging Visual Controls in Text Generation. CoRR abs/2205.02655 (2022) - 2021
- [j6]Lingpeng Kong, Yuanyuan Chen, Fengjiao Xu, Mingmin Xu, Zutan Li, Jingya Fang, Liangyun Zhang, Cong Pian:
Mining influential genes based on deep learning. BMC Bioinform. 22(1): 27 (2021) - [j5]Zutan Li, Hangjin Jiang
, Lingpeng Kong, Yuanyuan Chen, Kun Lang, Xiaodan Fan, Liangyun Zhang, Cong Pian:
Deep6mA: A deep learning framework for exploring similar patterns in DNA N6-methyladenine sites across different species. PLoS Comput. Biol. 17(2) (2021) - [j4]Dani Yogatama, Cyprien de Masson d'Autume, Lingpeng Kong:
Adaptive Semiparametric Language Models. Trans. Assoc. Comput. Linguistics 9: 362-373 (2021) - [c18]Lin Zheng, Zhiyong Wu, Lingpeng Kong:
Cascaded Head-colliding Attention. ACL/IJCNLP (1) 2021: 536-549 - [c17]Zhiyong Wu, Lingpeng Kong, Wei Bi, Xiang Li, Ben Kao:
Good for Misconceived Reasons: An Empirical Revisiting on the Need for Visual Context in Multimodal Machine Translation. ACL/IJCNLP (1) 2021: 6153-6166 - [c16]Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah A. Smith, Lingpeng Kong:
Random Feature Attention. ICLR 2021 - [i25]Dani Yogatama, Cyprien de Masson d'Autume, Lingpeng Kong:
Adaptive Semiparametric Language Models. CoRR abs/2102.02557 (2021) - [i24]Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah A. Smith, Lingpeng Kong:
Random Feature Attention. CoRR abs/2103.02143 (2021) - [i23]Zhiyong Wu, Lingpeng Kong, Wei Bi, Xiang Li, Ben Kao:
Good for Misconceived Reasons: An Empirical Revisiting on the Need for Visual Context in Multimodal Machine Translation. CoRR abs/2105.14462 (2021) - [i22]Lin Zheng, Zhiyong Wu, Lingpeng Kong:
Cascaded Head-colliding Attention. CoRR abs/2105.14850 (2021) - [i21]Lin Zheng, Huijie Pan, Lingpeng Kong:
Ripple Attention for Visual Perception with Sub-quadratic Complexity. CoRR abs/2110.02453 (2021) - [i20]Hao Peng, Jungo Kasai, Nikolaos Pappas, Dani Yogatama, Zhaofeng Wu, Lingpeng Kong, Roy Schwartz, Noah A. Smith:
ABC: Attention with Bounded-memory Control. CoRR abs/2110.02488 (2021) - [i19]Jakob Prange, Nathan Schneider, Lingpeng Kong:
Oracle Linguistic Graphs Complement a Pretrained Transformer Language Model: A Cross-formalism Comparison. CoRR abs/2112.07874 (2021) - 2020
- [j3]Lei Yu, Laurent Sartran, Wojciech Stokowiec, Wang Ling, Lingpeng Kong, Phil Blunsom, Chris Dyer:
Better Document-Level Machine Translation with Bayes' Rule. Trans. Assoc. Comput. Linguistics 8: 346-360 (2020) - [j2]Adhiguna Kuncoro, Lingpeng Kong, Daniel Fried, Dani Yogatama, Laura Rimell, Chris Dyer, Phil Blunsom:
Syntactic Structure Distillation Pretraining for Bidirectional Encoders. Trans. Assoc. Comput. Linguistics 8: 776-794 (2020) - [c15]Lingpeng Kong, Cyprien de Masson d'Autume, Lei Yu, Wang Ling, Zihang Dai, Dani Yogatama:
A Mutual Information Maximization Perspective of Language Representation Learning. ICLR 2020 - [i18]Adhiguna Kuncoro, Lingpeng Kong, Daniel Fried, Dani Yogatama, Laura Rimell, Chris Dyer, Phil Blunsom:
Syntactic Structure Distillation Pretraining For Bidirectional Encoders. CoRR abs/2005.13482 (2020)
2010 – 2019
- 2019
- [c14]Lingpeng Kong, Gábor Melis, Wang Ling, Lei Yu, Dani Yogatama:
Variational Smoothing in Recurrent Neural Network Language Models. ICLR (Poster) 2019 - [c13]Cyprien de Masson d'Autume, Sebastian Ruder, Lingpeng Kong, Dani Yogatama:
Episodic Memory in Lifelong Language Learning. NeurIPS 2019: 13122-13131 - [i17]Lingpeng Kong, Gábor Melis, Wang Ling, Lei Yu, Dani Yogatama:
Variational Smoothing in Recurrent Neural Network Language Models. CoRR abs/1901.09296 (2019) - [i16]Dani Yogatama, Cyprien de Masson d'Autume, Jerome T. Connor, Tomás Kociský, Mike Chrzanowski, Lingpeng Kong, Angeliki Lazaridou, Wang Ling, Lei Yu, Chris Dyer, Phil Blunsom:
Learning and Evaluating General Linguistic Intelligence. CoRR abs/1901.11373 (2019) - [i15]Cyprien de Masson d'Autume, Sebastian Ruder, Lingpeng Kong, Dani Yogatama:
Episodic Memory in Lifelong Language Learning. CoRR abs/1906.01076 (2019) - [i14]Lei Yu, Laurent Sartran, Wojciech Stokowiec, Wang Ling, Lingpeng Kong, Phil Blunsom, Chris Dyer:
Putting Machine Translation in Context with the Noisy Channel Model. CoRR abs/1910.00553 (2019) - [i13]Lingpeng Kong, Cyprien de Masson d'Autume, Wang Ling, Lei Yu, Zihang Dai, Dani Yogatama:
A Mutual Information Maximization Perspective of Language Representation Learning. CoRR abs/1910.08350 (2019) - 2018
- [i12]Jiangtao Feng, Lingpeng Kong, Po-Sen Huang, Chong Wang, Da Huang, Jiayuan Mao, Kan Qiao, Dengyong Zhou:
Neural Phrase-to-Phrase Machine Translation. CoRR abs/1811.02172 (2018) - [i11]Lei Yu, Cyprien de Masson d'Autume, Chris Dyer, Phil Blunsom, Lingpeng Kong, Wang Ling:
Sentence Encoding with Tree-constrained Relation Networks. CoRR abs/1811.10475 (2018) - 2017
- [j1]Hao Tang, Liang Lu, Lingpeng Kong, Kevin Gimpel, Karen Livescu, Chris Dyer, Noah A. Smith, Steve Renals:
End-to-End Neural Segmental Models for Speech Recognition. IEEE J. Sel. Top. Signal Process. 11(8): 1254-1264 (2017) - [c12]Adhiguna Kuncoro, Miguel Ballesteros, Lingpeng Kong, Chris Dyer, Graham Neubig, Noah A. Smith:
What Do Recurrent Neural Network Grammars Learn About Syntax? EACL (1) 2017: 1249-1258 - [c11]Liang Lu, Lingpeng Kong, Chris Dyer, Noah A. Smith:
Multitask Learning with CTC and Segmental CRF for Speech Recognition. INTERSPEECH 2017: 954-958 - [i10]Graham Neubig, Chris Dyer, Yoav Goldberg, Austin Matthews, Waleed Ammar, Antonios Anastasopoulos, Miguel Ballesteros, David Chiang, Daniel Clothiaux, Trevor Cohn, Kevin Duh, Manaal Faruqui, Cynthia Gan, Dan Garrette, Yangfeng Ji, Lingpeng Kong, Adhiguna Kuncoro, Gaurav Kumar, Chaitanya Malaviya, Paul Michel, Yusuke Oda, Matthew Richardson, Naomi Saphra, Swabha Swayamdipta, Pengcheng Yin:
DyNet: The Dynamic Neural Network Toolkit. CoRR abs/1701.03980 (2017) - [i9]Liang Lu, Lingpeng Kong, Chris Dyer, Noah A. Smith:
Multi-task Learning with CTC and Segmental CRF for Speech Recognition. CoRR abs/1702.06378 (2017) - [i8]Lingpeng Kong, Chris Alberti, Daniel Andor, Ivan Bogatyy, David Weiss:
DRAGNN: A Transition-based Framework for Dynamically Connected Neural Networks. CoRR abs/1703.04474 (2017) - [i7]Chris Alberti, Daniel Andor, Ivan Bogatyy, Michael Collins, Dan Gillick, Lingpeng Kong, Terry Koo, Ji Ma, Mark Omernick, Slav Petrov, Chayut Thanapirom, Zora Tung, David Weiss:
SyntaxNet Models for the CoNLL 2017 Shared Task. CoRR abs/1703.04929 (2017) - [i6]Hao Tang, Liang Lu, Lingpeng Kong, Kevin Gimpel, Karen Livescu, Chris Dyer, Noah A. Smith, Steve Renals:
End-to-End Neural Segmental Models for Speech Recognition. CoRR abs/1708.00531 (2017) - 2016
- [c10]Adhiguna Kuncoro, Miguel Ballesteros, Lingpeng Kong, Chris Dyer, Noah A. Smith:
Distilling an Ensemble of Greedy Dependency Parsers into One MST Parser. EMNLP 2016: 1744-1753 - [c9]Liang Lu, Lingpeng Kong, Chris Dyer, Noah A. Smith, Steve Renals:
Segmental Recurrent Neural Networks for End-to-End Speech Recognition. INTERSPEECH 2016: 385-389 - [c8]Lingpeng Kong, Chris Dyer, Noah A. Smith:
Segmental Recurrent Neural Networks. ICLR (Poster) 2016 - [i5]Liang Lu, Lingpeng Kong, Chris Dyer, Noah A. Smith, Steve Renals:
Segmental Recurrent Neural Networks for End-to-end Speech Recognition. CoRR abs/1603.00223 (2016) - [i4]Adhiguna Kuncoro, Miguel Ballesteros, Lingpeng Kong, Chris Dyer, Noah A. Smith:
Distilling an Ensemble of Greedy Dependency Parsers into One MST Parser. CoRR abs/1609.07561 (2016) - [i3]Adhiguna Kuncoro, Miguel Ballesteros, Lingpeng Kong, Chris Dyer, Graham Neubig, Noah A. Smith:
What Do Recurrent Neural Network Grammars Learn About Syntax? CoRR abs/1611.05774 (2016) - 2015
- [c7]Ting-Hao K. Huang, Yun-Nung Chen, Lingpeng Kong:
ACBiMA: Advanced Chinese Bi-Character Word Morphological Analyzer. SIGHAN@IJCNLP 2015: 26-31 - [c6]Dani Yogatama, Lingpeng Kong, Noah A. Smith:
Bayesian Optimization of Text Representations. EMNLP 2015: 2100-2105 - [c5]Lingpeng Kong, Alexander M. Rush, Noah A. Smith:
Transforming Dependencies into Phrase Structures. HLT-NAACL 2015: 788-798 - [i2]Yangfeng Ji, Trevor Cohn, Lingpeng Kong, Chris Dyer, Jacob Eisenstein:
Document Context Language Models. CoRR abs/1511.03962 (2015) - 2014
- [c4]Lingpeng Kong, Nathan Schneider, Swabha Swayamdipta, Archna Bhatia, Chris Dyer, Noah A. Smith:
A Dependency Parser for Tweets. EMNLP 2014: 1001-1012 - [c3]William Yang Wang, Lingpeng Kong, Kathryn Mazaitis, William W. Cohen:
Dependency Parsing for Weibo: An Efficient Probabilistic Logic Programming Approach. EMNLP 2014: 1152-1158 - [i1]Lingpeng Kong, Noah A. Smith:
An Empirical Comparison of Parsing Methods for Stanford Dependencies. CoRR abs/1404.4314 (2014) - 2011
- [c2]Likun Qiu, Lei Wu, Kai Zhao, Changjian Hu, Lingpeng Kong:
Improving Chinese Dependency Parsing with Self-Disambiguating Patterns. IALP 2011: 7-10 - [c1]Lingpeng Kong, Likun Qiu:
Formalization and Rules for Recognition of Satirical Irony. IALP 2011: 135-138
Coauthor Index
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