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Kevin Gimpel
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Journal Articles
- 2019
- [j5]Aynaz Taheri, Kevin Gimpel, Tanya Y. Berger-Wolf:
Sequence-to-sequence modeling for graph representation learning. Appl. Netw. Sci. 4(1): 68:1-68:26 (2019) - 2017
- [j4]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) - 2015
- [j3]Jing Wang, Mohit Bansal, Kevin Gimpel, Brian D. Ziebart, Clement T. Yu:
A Sense-Topic Model for Word Sense Induction with Unsupervised Data Enrichment. Trans. Assoc. Comput. Linguistics 3: 59-71 (2015) - [j2]John Wieting, Mohit Bansal, Kevin Gimpel, Karen Livescu:
From Paraphrase Database to Compositional Paraphrase Model and Back. Trans. Assoc. Comput. Linguistics 3: 345-358 (2015) - 2014
- [j1]Kevin Gimpel, Noah A. Smith:
Phrase Dependency Machine Translation with Quasi-Synchronous Tree-to-Tree Features. Comput. Linguistics 40(2): 349-401 (2014)
Conference and Workshop Papers
- 2023
- [c92]Cheng-I Jeff Lai, Freda Shi, Puyuan Peng, Yoon Kim, Kevin Gimpel, Shiyu Chang, Yung-Sung Chuang, Saurabhchand Bhati, David D. Cox, David Harwath, Yang Zhang, Karen Livescu, James R. Glass:
Audio-Visual Neural Syntax Acquisition. ASRU 2023: 1-8 - [c91]Lingyu Gao, Debanjan Ghosh, Kevin Gimpel:
The Benefits of Label-Description Training for Zero-Shot Text Classification. EMNLP 2023: 13823-13844 - 2022
- [c90]Vikram Gupta, Haoyue Shi, Kevin Gimpel, Mrinmaya Sachan:
Deep Clustering of Text Representations for Supervision-Free Probing of Syntax. AAAI 2022: 10720-10728 - [c89]Shubham Toshniwal, Sam Wiseman, Karen Livescu, Kevin Gimpel:
Chess as a Testbed for Language Model State Tracking. AAAI 2022: 11385-11393 - [c88]Freda Shi, Kevin Gimpel, Karen Livescu:
Substructure Distribution Projection for Zero-Shot Cross-Lingual Dependency Parsing. ACL (1) 2022: 6547-6563 - [c87]Mingda Chen, Zewei Chu, Sam Wiseman, Kevin Gimpel:
SummScreen: A Dataset for Abstractive Screenplay Summarization. ACL (1) 2022: 8602-8615 - [c86]John Wieting, Kevin Gimpel, Graham Neubig, Taylor Berg-Kirkpatrick:
Paraphrastic Representations at Scale. EMNLP (Demos) 2022: 379-388 - [c85]Shubham Toshniwal, Sam Wiseman, Karen Livescu, Kevin Gimpel:
Baked-in State Probing. EMNLP (Findings) 2022: 5430-5435 - [c84]Yeshu Li, Danyal Saeed, Xinhua Zhang, Brian D. Ziebart, Kevin Gimpel:
Moment Distributionally Robust Tree Structured Prediction. NeurIPS 2022 - [c83]Lingyu Gao, Debanjan Ghosh, Kevin Gimpel:
"What makes a question inquisitive?" A Study on Type-Controlled Inquisitive Question Generation. *SEM@NAACL-HLT 2022: 240-257 - 2021
- [c82]Mingda Chen, Sam Wiseman, Kevin Gimpel:
WikiTableT: A Large-Scale Data-to-Text Dataset for Generating Wikipedia Article Sections. ACL/IJCNLP (Findings) 2021: 193-209 - [c81]Haoyue Shi, Karen Livescu, Kevin Gimpel:
Substructure Substitution: Structured Data Augmentation for NLP. ACL/IJCNLP (Findings) 2021: 3494-3508 - [c80]Zewei Chu, Karl Stratos, Kevin Gimpel:
Unsupervised Label Refinement Improves Dataless Text Classification. ACL/IJCNLP (Findings) 2021: 4165-4178 - [c79]Zewei Chu, Karl Stratos, Kevin Gimpel:
NATCAT: Weakly Supervised Text Classification with Naturally Annotated Resources. AKBC 2021 - [c78]Davis Yoshida, Kevin Gimpel:
Reconsidering the Past: Optimizing Hidden States in Language Models. EMNLP (Findings) 2021: 4099-4105 - [c77]Xiaoan Ding, Kevin Gimpel:
FlowPrior: Learning Expressive Priors for Latent Variable Sentence Models. NAACL-HLT 2021: 3242-3258 - 2020
- [c76]Zewei Chu, Mingda Chen, Jing Chen, Miaosen Wang, Kevin Gimpel, Manaal Faruqui, Xiance Si:
How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions. AAAI 2020: 7586-7593 - [c75]Lifu Tu, Richard Yuanzhe Pang, Sam Wiseman, Kevin Gimpel:
ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation. ACL 2020: 2819-2826 - [c74]Shubham Toshniwal, Allyson Ettinger, Kevin Gimpel, Karen Livescu:
PeTra: A Sparsely Supervised Memory Model for People Tracking. ACL 2020: 5415-5428 - [c73]Lifu Tu, Richard Yuanzhe Pang, Kevin Gimpel:
Improving Joint Training of Inference Networks and Structured Prediction Energy Networks. SPNLP@EMNLP 2020: 62-73 - [c72]Lingyu Gao, Kevin Gimpel, Arnar Thor Jensson:
Distractor Analysis and Selection for Multiple-Choice Cloze Questions for Second-Language Learners. BEA@ACL 2020: 102-114 - [c71]Mingda Chen, Zewei Chu, Karl Stratos, Kevin Gimpel:
Mining Knowledge for Natural Language Inference from Wikipedia Categories. EMNLP (Findings) 2020: 3500-3511 - [c70]Lifu Tu, Tianyu Liu, Kevin Gimpel:
An Exploration of Arbitrary-Order Sequence Labeling via Energy-Based Inference Networks. EMNLP (1) 2020: 5569-5582 - [c69]Haoyue Shi, Karen Livescu, Kevin Gimpel:
On the Role of Supervision in Unsupervised Constituency Parsing. EMNLP (1) 2020: 7611-7621 - [c68]Xiaoan Ding, Tianyu Liu, Baobao Chang, Zhifang Sui, Kevin Gimpel:
Discriminatively-Tuned Generative Classifiers for Robust Natural Language Inference. EMNLP (1) 2020: 8189-8202 - [c67]Shubham Toshniwal, Sam Wiseman, Allyson Ettinger, Karen Livescu, Kevin Gimpel:
Learning to Ignore: Long Document Coreference with Bounded Memory Neural Networks. EMNLP (1) 2020: 8519-8526 - [c66]Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut:
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations. ICLR 2020 - [c65]Mingda Chen, Kevin Gimpel:
Learning Probabilistic Sentence Representations from Paraphrases. RepL4NLP@ACL 2020: 17-23 - [c64]Shubham Toshniwal, Haoyue Shi, Bowen Shi, Lingyu Gao, Karen Livescu, Kevin Gimpel:
A Cross-Task Analysis of Text Span Representations. RepL4NLP@ACL 2020: 166-176 - 2019
- [c63]Haoyue Shi, Jiayuan Mao, Kevin Gimpel, Karen Livescu:
Visually Grounded Neural Syntax Acquisition. ACL (1) 2019: 1842-1861 - [c62]John Wieting, Taylor Berg-Kirkpatrick, Kevin Gimpel, Graham Neubig:
Beyond BLEU: Training Neural Machine Translation with Semantic Similarity. ACL (1) 2019: 4344-4355 - [c61]John Wieting, Kevin Gimpel, Graham Neubig, Taylor Berg-Kirkpatrick:
Simple and Effective Paraphrastic Similarity from Parallel Translations. ACL (1) 2019: 4602-4608 - [c60]Mingda Chen, Qingming Tang, Sam Wiseman, Kevin Gimpel:
Controllable Paraphrase Generation with a Syntactic Exemplar. ACL (1) 2019: 5972-5984 - [c59]Lifu Tu, Xiaoan Ding, Dong Yu, Kevin Gimpel:
Generating Diverse Story Continuations with Controllable Semantics. NGT@EMNLP-IJCNLP 2019: 44-58 - [c58]Richard Yuanzhe Pang, Kevin Gimpel:
Unsupervised Evaluation Metrics and Learning Criteria for Non-Parallel Textual Transfer. NGT@EMNLP-IJCNLP 2019: 138-147 - [c57]Mingda Chen, Zewei Chu, Yang Chen, Karl Stratos, Kevin Gimpel:
EntEval: A Holistic Evaluation Benchmark for Entity Representations. EMNLP/IJCNLP (1) 2019: 421-433 - [c56]Xiaoan Ding, Kevin Gimpel:
Latent-Variable Generative Models for Data-Efficient Text Classification. EMNLP/IJCNLP (1) 2019: 507-517 - [c55]Mingda Chen, Zewei Chu, Kevin Gimpel:
Evaluation Benchmarks and Learning Criteria for Discourse-Aware Sentence Representations. EMNLP/IJCNLP (1) 2019: 649-662 - [c54]Jun Seok Kang, Robert L. Logan IV, Zewei Chu, Yang Chen, Dheeru Dua, Kevin Gimpel, Sameer Singh, Niranjan Balasubramanian:
PoMo: Generating Entity-Specific Post-Modifiers in Context. NAACL-HLT (1) 2019: 826-838 - [c53]Mingda Chen, Qingming Tang, Sam Wiseman, Kevin Gimpel:
A Multi-Task Approach for Disentangling Syntax and Semantics in Sentence Representations. NAACL-HLT (1) 2019: 2453-2464 - [c52]Lifu Tu, Kevin Gimpel:
Benchmarking Approximate Inference Methods for Neural Structured Prediction. NAACL-HLT (1) 2019: 3313-3324 - [c51]Aynaz Taheri, Kevin Gimpel, Tanya Y. Berger-Wolf:
Learning to Represent the Evolution of Dynamic Graphs with Recurrent Models. WWW (Companion Volume) 2019: 301-307 - 2018
- [c50]John Wieting, Kevin Gimpel:
ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations. ACL (1) 2018: 451-462 - [c49]Mingda Chen, Qingming Tang, Karen Livescu, Kevin Gimpel:
Variational Sequential Labelers for Semi-Supervised Learning. EMNLP 2018: 215-226 - [c48]Kalpesh Krishna, Liang Lu, Kevin Gimpel, Karen Livescu:
A Study of All-Convolutional Encoders for Connectionist Temporal Classification. ICASSP 2018: 5814-5818 - [c47]Lifu Tu, Kevin Gimpel:
Learning Approximate Inference Networks for Structured Prediction. ICLR (Poster) 2018 - [c46]Trang Tran, Shubham Toshniwal, Mohit Bansal, Kevin Gimpel, Karen Livescu, Mari Ostendorf:
Parsing Speech: a Neural Approach to Integrating Lexical and Acoustic-Prosodic Information. NAACL-HLT 2018: 69-81 - [c45]Mingda Chen, Kevin Gimpel:
Smaller Text Classifiers with Discriminative Cluster Embeddings. NAACL-HLT (2) 2018: 739-745 - [c44]Mohit Iyyer, John Wieting, Kevin Gimpel, Luke Zettlemoyer:
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks. NAACL-HLT 2018: 1875-1885 - [c43]Dan Hendrycks, Mantas Mazeika, Duncan Wilson, Kevin Gimpel:
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise. NeurIPS 2018: 10477-10486 - [c42]Manasvi Sagarkar, John Wieting, Lifu Tu, Kevin Gimpel:
Quality Signals in Generated Stories. *SEM@NAACL-HLT 2018: 192-202 - 2017
- [c41]Zheng Cai, Lifu Tu, Kevin Gimpel:
Pay Attention to the Ending: Strong Neural Baselines for the ROC Story Cloze Task. ACL (2) 2017: 616-622 - [c40]John Wieting, Kevin Gimpel:
Revisiting Recurrent Networks for Paraphrastic Sentence Embeddings. ACL (1) 2017: 2078-2088 - [c39]Zewei Chu, Hai Wang, Kevin Gimpel, David A. McAllester:
Broad Context Language Modeling as Reading Comprehension. EACL (2) 2017: 52-57 - [c38]John Wieting, Jonathan Mallinson, Kevin Gimpel:
Learning Paraphrastic Sentence Embeddings from Back-Translated Bitext. EMNLP 2017: 274-285 - [c37]Dan Hendrycks, Kevin Gimpel:
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks. ICLR (Poster) 2017 - [c36]Dan Hendrycks, Kevin Gimpel:
Early Methods for Detecting Adversarial Images. ICLR (Workshop) 2017 - [c35]Hai Wang, Takeshi Onishi, Kevin Gimpel, David A. McAllester:
Emergent Predication Structure in Hidden State Vectors of Neural Readers. Rep4NLP@ACL 2017: 26-36 - [c34]Lifu Tu, Kevin Gimpel, Karen Livescu:
Learning to Embed Words in Context for Syntactic Tasks. Rep4NLP@ACL 2017: 265-275 - 2016
- [c33]Xiang Li, Aynaz Taheri, Lifu Tu, Kevin Gimpel:
Commonsense Knowledge Base Completion. ACL (1) 2016 - [c32]John Wieting, Mohit Bansal, Kevin Gimpel, Karen Livescu:
Charagram: Embedding Words and Sentences via Character n-grams. EMNLP 2016: 1504-1515 - [c31]Takeshi Onishi, Hai Wang, Mohit Bansal, Kevin Gimpel, David A. McAllester:
Who did What: A Large-Scale Person-Centered Cloze Dataset. EMNLP 2016: 2230-2235 - [c30]Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu:
Efficient Segmental Cascades for Speech Recognition. INTERSPEECH 2016: 1903-1907 - [c29]Yaniv Tenzer, Alexander G. Schwing, Kevin Gimpel, Tamir Hazan:
Constraints Based Convex Belief Propagation. NIPS 2016: 2532-2540 - [c28]Pranava Swaroop Madhyastha, Mohit Bansal, Kevin Gimpel, Karen Livescu:
Mapping Unseen Words to Task-Trained Embedding Spaces. Rep4NLP@ACL 2016: 100-110 - [c27]Hua He, John Wieting, Kevin Gimpel, Jinfeng Rao, Jimmy Lin:
UMD-TTIC-UW at SemEval-2016 Task 1: Attention-Based Multi-Perspective Convolutional Neural Networks for Textual Similarity Measurement. SemEval@NAACL-HLT 2016: 1103-1108 - [c26]Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu:
End-to-end training approaches for discriminative segmental models. SLT 2016: 496-502 - [c25]John Wieting, Mohit Bansal, Kevin Gimpel, Karen Livescu:
Towards Universal Paraphrastic Sentence Embeddings. ICLR 2016 - 2015
- [c24]Hai Wang, Mohit Bansal, Kevin Gimpel, David A. McAllester:
Machine Comprehension with Syntax, Frames, and Semantics. ACL (2) 2015: 700-706 - [c23]Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu:
Discriminative segmental cascades for feature-rich phone recognition. ASRU 2015: 561-568 - [c22]Hua He, Kevin Gimpel, Jimmy Lin:
Multi-Perspective Sentence Similarity Modeling with Convolutional Neural Networks. EMNLP 2015: 1576-1586 - [c21]Ang Lu, Weiran Wang, Mohit Bansal, Kevin Gimpel, Karen Livescu:
Deep Multilingual Correlation for Improved Word Embeddings. HLT-NAACL 2015: 250-256 - 2014
- [c20]Mohit Bansal, Kevin Gimpel, Karen Livescu:
Tailoring Continuous Word Representations for Dependency Parsing. ACL (2) 2014: 809-815 - [c19]Kevin Gimpel, Mohit Bansal:
Weakly-Supervised Learning with Cost-Augmented Contrastive Estimation. EMNLP 2014: 1329-1341 - [c18]Hao Tang, Kevin Gimpel, Karen Livescu:
A comparison of training approaches for discriminative segmental models. INTERSPEECH 2014: 1219-1223 - 2013
- [c17]Kevin Gimpel, Dhruv Batra, Chris Dyer, Gregory Shakhnarovich:
A Systematic Exploration of Diversity in Machine Translation. EMNLP 2013: 1100-1111 - [c16]Olutobi Owoputi, Brendan O'Connor, Chris Dyer, Kevin Gimpel, Nathan Schneider, Noah A. Smith:
Improved Part-of-Speech Tagging for Online Conversational Text with Word Clusters. HLT-NAACL 2013: 380-390 - [c15]Shiladitya Sinha, Chris Dyer, Kevin Gimpel, Noah A. Smith:
Predicting the NFL using Twitter. MLSA@PKDD/ECML 2013: 28-38 - 2012
- [c14]Victor Chahuneau, Kevin Gimpel, Bryan R. Routledge, Lily Scherlis, Noah A. Smith:
Word Salad: Relating Food Prices and Descriptions. EMNLP-CoNLL 2012: 1357-1367 - [c13]Kevin Gimpel, Noah A. Smith:
Structured Ramp Loss Minimization for Machine Translation. HLT-NAACL 2012: 221-231 - [c12]Kevin Gimpel, Noah A. Smith:
Concavity and Initialization for Unsupervised Dependency Parsing. HLT-NAACL 2012: 577-581 - 2011
- [c11]Kevin Gimpel, Nathan Schneider, Brendan O'Connor, Dipanjan Das, Daniel Mills, Jacob Eisenstein, Michael Heilman, Dani Yogatama, Jeffrey Flanigan, Noah A. Smith:
Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments. ACL (2) 2011: 42-47 - [c10]Kevin Gimpel, Noah A. Smith:
Quasi-Synchronous Phrase Dependency Grammars for Machine Translation. EMNLP 2011: 474-485 - [c9]Chris Dyer, Kevin Gimpel, Jonathan H. Clark, Noah A. Smith:
The CMU-ARK German-English Translation System. WMT@EMNLP 2011: 337-343 - [c8]Kevin Gimpel, Noah A. Smith:
Generative Models of Monolingual and Bilingual Gappy Patterns. WMT@EMNLP 2011: 512-522 - 2010
- [c7]Kevin Gimpel, Dipanjan Das, Noah A. Smith:
Distributed Asynchronous Online Learning for Natural Language Processing. CoNLL 2010: 213-222 - [c6]Mahesh Joshi, Dipanjan Das, Kevin Gimpel, Noah A. Smith:
Movie Reviews and Revenues: An Experiment in Text Regression. HLT-NAACL 2010: 293-296 - [c5]Kevin Gimpel, Noah A. Smith:
Softmax-Margin CRFs: Training Log-Linear Models with Cost Functions. HLT-NAACL 2010: 733-736 - 2009
- [c4]Kevin Gimpel, Noah A. Smith:
Cube Summing, Approximate Inference with Non-Local Features, and Dynamic Programming without Semirings. EACL 2009: 318-326 - [c3]Kevin Gimpel, Noah A. Smith:
Feature-Rich Translation by Quasi-Synchronous Lattice Parsing. EMNLP 2009: 219-228 - 2008
- [c2]Shay B. Cohen, Kevin Gimpel, Noah A. Smith:
Logistic Normal Priors for Unsupervised Probabilistic Grammar Induction. NIPS 2008: 321-328 - [c1]Kevin Gimpel, Noah A. Smith:
Rich Source-Side Context for Statistical Machine Translation. WMT@ACL 2008: 9-17
Informal and Other Publications
- 2024
- [i70]Freda Shi, Kevin Gimpel, Karen Livescu:
Structured Tree Alignment for Evaluation of (Speech) Constituency Parsing. CoRR abs/2402.13433 (2024) - 2023
- [i69]Lingyu Gao, Debanjan Ghosh, Kevin Gimpel:
The Benefits of Label-Description Training for Zero-Shot Text Classification. CoRR abs/2305.02239 (2023) - [i68]Cheng-I Jeff Lai, Freda Shi, Puyuan Peng, Yoon Kim, Kevin Gimpel, Shiyu Chang, Yung-Sung Chuang, Saurabhchand Bhati, David D. Cox, David Harwath, Yang Zhang, Karen Livescu, James R. Glass:
Audio-Visual Neural Syntax Acquisition. CoRR abs/2310.07654 (2023) - [i67]Davis Yoshida, Kartik Goyal, Kevin Gimpel:
MAP's not dead yet: Uncovering true language model modes by conditioning away degeneracy. CoRR abs/2311.08817 (2023) - [i66]Yixiao Song, Kalpesh Krishna, Rajesh Bhatt, Kevin Gimpel, Mohit Iyyer:
GEE! Grammar Error Explanation with Large Language Models. CoRR abs/2311.09517 (2023) - 2022
- [i65]Lingyu Gao, Debanjan Ghosh, Kevin Gimpel:
"What makes a question inquisitive?" A Study on Type-Controlled Inquisitive Question Generation. CoRR abs/2205.08056 (2022) - 2021
- [i64]Haoyue Shi, Karen Livescu, Kevin Gimpel:
Substructure Substitution: Structured Data Augmentation for NLP. CoRR abs/2101.00411 (2021) - [i63]Shubham Toshniwal, Sam Wiseman, Karen Livescu, Kevin Gimpel:
Learning Chess Blindfolded: Evaluating Language Models on State Tracking. CoRR abs/2102.13249 (2021) - [i62]Mingda Chen, Zewei Chu, Sam Wiseman, Kevin Gimpel:
SummScreen: A Dataset for Abstractive Screenplay Summarization. CoRR abs/2104.07091 (2021) - [i61]John Wieting, Kevin Gimpel, Graham Neubig, Taylor Berg-Kirkpatrick:
Paraphrastic Representations at Scale. CoRR abs/2104.15114 (2021) - [i60]Mingda Chen, Kevin Gimpel:
TVRecap: A Dataset for Generating Stories with Character Descriptions. CoRR abs/2109.08833 (2021) - [i59]Shubham Toshniwal, Patrick Xia, Sam Wiseman, Karen Livescu, Kevin Gimpel:
On Generalization in Coreference Resolution. CoRR abs/2109.09667 (2021) - [i58]Haoyue Shi, Kevin Gimpel, Karen Livescu:
Substructure Distribution Projection for Zero-Shot Cross-Lingual Dependency Parsing. CoRR abs/2110.08538 (2021) - [i57]Davis Yoshida, Kevin Gimpel:
Reconsidering the Past: Optimizing Hidden States in Language Models. CoRR abs/2112.08653 (2021) - 2020
- [i56]Lifu Tu, Richard Yuanzhe Pang, Sam Wiseman, Kevin Gimpel:
ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation. CoRR abs/2005.00850 (2020) - [i55]Shubham Toshniwal, Allyson Ettinger, Kevin Gimpel, Karen Livescu:
PeTra: A Sparsely Supervised Memory Model for People Tracking. CoRR abs/2005.02990 (2020) - [i54]Mingda Chen, Kevin Gimpel:
Learning Probabilistic Sentence Representations from Paraphrases. CoRR abs/2005.08105 (2020) - [i53]Shubham Toshniwal, Haoyue Shi, Bowen Shi, Lingyu Gao, Karen Livescu, Kevin Gimpel:
A Cross-Task Analysis of Text Span Representations. CoRR abs/2006.03866 (2020) - [i52]Davis Yoshida, Allyson Ettinger, Kevin Gimpel:
Adding Recurrence to Pretrained Transformers for Improved Efficiency and Context Size. CoRR abs/2008.07027 (2020) - [i51]Zewei Chu, Karl Stratos, Kevin Gimpel:
Natcat: Weakly Supervised Text Classification with Naturally Annotated Datasets. CoRR abs/2009.14335 (2020) - [i50]Mingda Chen, Zewei Chu, Karl Stratos, Kevin Gimpel:
Mining Knowledge for Natural Language Inference from Wikipedia Categories. CoRR abs/2010.01239 (2020) - [i49]Haoyue Shi, Karen Livescu, Kevin Gimpel:
On the Role of Supervision in Unsupervised Constituency Parsing. CoRR abs/2010.02423 (2020) - [i48]Lifu Tu, Tianyu Liu, Kevin Gimpel:
An Exploration of Arbitrary-Order Sequence Labeling via Energy-Based Inference Networks. CoRR abs/2010.02789 (2020) - [i47]Shubham Toshniwal, Sam Wiseman, Allyson Ettinger, Karen Livescu, Kevin Gimpel:
Learning to Ignore: Long Document Coreference with Bounded Memory Neural Networks. CoRR abs/2010.02807 (2020) - [i46]Xiaoan Ding, Tianyu Liu, Baobao Chang, Zhifang Sui, Kevin Gimpel:
Discriminatively-Tuned Generative Classifiers for Robust Natural Language Inference. CoRR abs/2010.03760 (2020) - [i45]Mingda Chen, Sam Wiseman, Kevin Gimpel:
Controllable Paraphrasing and Translation with a Syntactic Exemplar. CoRR abs/2010.05856 (2020) - [i44]Vikram Gupta, Haoyue Shi, Kevin Gimpel, Mrinmaya Sachan:
Clustering Contextualized Representations of Text for Unsupervised Syntax Induction. CoRR abs/2010.12784 (2020) - [i43]Zewei Chu, Karl Stratos, Kevin Gimpel:
Unsupervised Label Refinement Improves Dataless Text Classification. CoRR abs/2012.04194 (2020) - [i42]Mingda Chen, Sam Wiseman, Kevin Gimpel:
Generating Wikipedia Article Sections from Diverse Data Sources. CoRR abs/2012.14919 (2020) - 2019
- [i41]Lifu Tu, Kevin Gimpel:
Benchmarking Approximate Inference Methods for Neural Structured Prediction. CoRR abs/1904.01138 (2019) - [i40]Mingda Chen, Qingming Tang, Sam Wiseman, Kevin Gimpel:
A Multi-Task Approach for Disentangling Syntax and Semantics in Sentence Representations. CoRR abs/1904.01173 (2019) - [i39]Jun Seok Kang, Robert L. Logan IV, Zewei Chu, Yang Chen, Dheeru Dua, Kevin Gimpel, Sameer Singh, Niranjan Balasubramanian:
PoMo: Generating Entity-Specific Post-Modifiers in Context. CoRR abs/1904.03111 (2019) - [i38]Mingda Chen, Qingming Tang, Sam Wiseman, Kevin Gimpel:
Controllable Paraphrase Generation with a Syntactic Exemplar. CoRR abs/1906.00565 (2019) - [i37]Haoyue Shi, Jiayuan Mao, Kevin Gimpel, Karen Livescu:
Visually Grounded Neural Syntax Acquisition. CoRR abs/1906.02890 (2019) - [i36]Mingda Chen, Kevin Gimpel:
Smaller Text Classifiers with Discriminative Cluster Embeddings. CoRR abs/1906.09532 (2019) - [i35]Mingda Chen, Qingming Tang, Karen Livescu, Kevin Gimpel:
Variational Sequential Labelers for Semi-Supervised Learning. CoRR abs/1906.09535 (2019) - [i34]Mingda Chen, Zewei Chu, Yang Chen, Karl Stratos, Kevin Gimpel:
EntEval: A Holistic Evaluation Benchmark for Entity Representations. CoRR abs/1909.00137 (2019) - [i33]Mingda Chen, Zewei Chu, Kevin Gimpel:
Evaluation Benchmarks and Learning Criteriafor Discourse-Aware Sentence Representations. CoRR abs/1909.00142 (2019) - [i32]John Wieting, Taylor Berg-Kirkpatrick, Kevin Gimpel, Graham Neubig:
Beyond BLEU: Training Neural Machine Translation with Semantic Similarity. CoRR abs/1909.06694 (2019) - [i31]Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut:
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations. CoRR abs/1909.11942 (2019) - [i30]Lifu Tu, Xiaoan Ding, Dong Yu, Kevin Gimpel:
Generating Diverse Story Continuations with Controllable Semantics. CoRR abs/1909.13434 (2019) - [i29]John Wieting, Kevin Gimpel, Graham Neubig, Taylor Berg-Kirkpatrick:
Simple and Effective Paraphrastic Similarity from Parallel Translations. CoRR abs/1909.13872 (2019) - [i28]Xiaoan Ding, Kevin Gimpel:
Latent-Variable Generative Models for Data-Efficient Text Classification. CoRR abs/1910.00382 (2019) - [i27]Lifu Tu, Richard Yuanzhe Pang, Kevin Gimpel:
Improving Joint Training of Inference Networks and Structured Prediction Energy Networks. CoRR abs/1911.02891 (2019) - [i26]Zewei Chu, Mingda Chen, Jing Chen, Miaosen Wang, Kevin Gimpel, Manaal Faruqui, Xiance Si:
How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions. CoRR abs/1911.09247 (2019) - 2018
- [i25]Dan Hendrycks, Mantas Mazeika, Duncan Wilson, Kevin Gimpel:
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise. CoRR abs/1802.05300 (2018) - [i24]Lifu Tu, Kevin Gimpel:
Learning Approximate Inference Networks for Structured Prediction. CoRR abs/1803.03376 (2018) - [i23]Mohit Iyyer, John Wieting, Kevin Gimpel, Luke Zettlemoyer:
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks. CoRR abs/1804.06059 (2018) - [i22]Richard Yuanzhe Pang, Kevin Gimpel:
Learning Criteria and Evaluation Metrics for Textual Transfer between Non-Parallel Corpora. CoRR abs/1810.11878 (2018) - 2017
- [i21]Trang Tran, Shubham Toshniwal, Mohit Bansal, Kevin Gimpel, Karen Livescu, Mari Ostendorf:
Joint Modeling of Text and Acoustic-Prosodic Cues for Neural Parsing. CoRR abs/1704.07287 (2017) - [i20]John Wieting, Kevin Gimpel:
Revisiting Recurrent Networks for Paraphrastic Sentence Embeddings. CoRR abs/1705.00364 (2017) - [i19]John Wieting, Jonathan Mallinson, Kevin Gimpel:
Learning Paraphrastic Sentence Embeddings from Back-Translated Bitext. CoRR abs/1706.01847 (2017) - [i18]Lifu Tu, Kevin Gimpel, Karen Livescu:
Learning to Embed Words in Context for Syntactic Tasks. CoRR abs/1706.02807 (2017) - [i17]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) - [i16]Kalpesh Krishna, Liang Lu, Kevin Gimpel, Karen Livescu:
A Study of All-Convolutional Encoders for Connectionist Temporal Classification. CoRR abs/1710.10398 (2017) - [i15]John Wieting, Kevin Gimpel:
Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations. CoRR abs/1711.05732 (2017) - 2016
- [i14]Dan Hendrycks, Kevin Gimpel:
Bridging Nonlinearities and Stochastic Regularizers with Gaussian Error Linear Units. CoRR abs/1606.08415 (2016) - [i13]Dan Hendrycks, Kevin Gimpel:
Generalizing and Improving Weight Initialization. CoRR abs/1607.02488 (2016) - [i12]John Wieting, Mohit Bansal, Kevin Gimpel, Karen Livescu:
Charagram: Embedding Words and Sentences via Character n-grams. CoRR abs/1607.02789 (2016) - [i11]Dan Hendrycks, Kevin Gimpel:
Visible Progress on Adversarial Images and a New Saliency Map. CoRR abs/1608.00530 (2016) - [i10]Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu:
Efficient Segmental Cascades for Speech Recognition. CoRR abs/1608.00929 (2016) - [i9]Takeshi Onishi, Hai Wang, Mohit Bansal, Kevin Gimpel, David A. McAllester:
Who did What: A Large-Scale Person-Centered Cloze Dataset. CoRR abs/1608.05457 (2016) - [i8]Dan Hendrycks, Kevin Gimpel:
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks. CoRR abs/1610.02136 (2016) - [i7]Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu:
End-to-End Training Approaches for Discriminative Segmental Models. CoRR abs/1610.06700 (2016) - [i6]Zewei Chu, Hai Wang, Kevin Gimpel, David A. McAllester:
Broad Context Language Modeling as Reading Comprehension. CoRR abs/1610.08431 (2016) - [i5]Hai Wang, Takeshi Onishi, Kevin Gimpel, David A. McAllester:
Emergent Logical Structure in Vector Representations of Neural Readers. CoRR abs/1611.07954 (2016) - 2015
- [i4]John Wieting, Mohit Bansal, Kevin Gimpel, Karen Livescu:
From Paraphrase Database to Compositional Paraphrase Model and Back. CoRR abs/1506.03487 (2015) - [i3]Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu:
Discriminative Segmental Cascades for Feature-Rich Phone Recognition. CoRR abs/1507.06073 (2015) - [i2]Pranava Swaroop Madhyastha, Mohit Bansal, Kevin Gimpel, Karen Livescu:
Mapping Unseen Words to Task-Trained Embedding Spaces. CoRR abs/1510.02387 (2015) - 2013
- [i1]Shiladitya Sinha, Chris Dyer, Kevin Gimpel, Noah A. Smith:
Predicting the NFL using Twitter. CoRR abs/1310.6998 (2013)
Coauthor Index
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