Publications
2023
- Robustification of Multilingual Language Models to Real-world Noise in Crosslingual Zero-shot Settings with Robust Contrastive Pretraining.
Asa Cooper Stickland*, Sailik Sengupta*, Jason Krone, He He and Saab Mansour. The European Chapter of the Association for Computational Linguistics (EACL), 2023. [bib] [code] - Language Models are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought.
Abulhair Saparov and He He. International Conference on Learning Representations (ICLR), 2023. [bib] [code]
2022
- Reward Gaming in Conditional Text Generation.
Richard Yuanzhe Pang, Vishakh Padmakumar, Thibault Sellam, Ankur P Parikh and He He. arXiv:2211.08714 preprint, 2022. [bib] - Are All Spurious Features in Natural Language Alike? An Analysis through a Causal Lens.
Nitish Joshi, Xiang Pan and He He. Empirical Methods in Natural Language Processing (EMNLP), 2022. [bib] [code] - Help me write a poem: Instruction Tuning as a Vehicle for Collaborative Poetry Writing.
Tuhin Chakrabarty, Vishakh Padmakumar and He He. Empirical Methods in Natural Language Processing (EMNLP), 2022. [bib] [code] [project] - Improving Faithfulness by Augmenting Negative Summaries from Fake Documents.
Tianshu Wang, Faisal Ladhak, Esin Durmus and He He. Empirical Methods in Natural Language Processing (EMNLP), 2022. [bib] [code] - On the Relation between Sensitivity and Accuracy in In-context Learning.
Yanda Chen, Chen Zhao, Zhou Yu, Kathleen McKeown and He He. arXiv:2209.07661 preprint, 2022. [bib] - SeqPATE: Differentially Private Text Generation via Knowledge Distillation.
Zhiliang Tian, Yingxiu Zhao, Ziyue Huang, Yu-Xiang Wang, Nevin Zhang and He He. Neural Information Processing Systems (NeurIPS), 2022. [bib] - Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation.
Aahlad Puli, Nitish Joshi, He He and Rajesh Ranganath. arXiv:2210.01302 preprint, 2022. [bib] - Amortized Noisy Channel Neural Machine Translation.
Richard Yuanzhe Pang, He He and Kyunghyun Cho. International Natural Language Generation Conference (INLG), 2022. [bib] - {QuALITY}: Question Answering with Long Input Texts, Yes!.
Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, Nikita Nangia, Jason Phang, Angelica Chen, Vishakh Padmakumar, Johnny Ma, Jana Thompson, He He and Sam Bowman. North American Chapter of the Association for Computational Linguistics (NAACL), 2022. [bib] [code] - Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning.
Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He and George Karypis. North American Chapter of the Association for Computational Linguistics (NAACL), 2022. [bib] - Machine-in-the-Loop Rewriting for Creative Image Captioning.
Vishakh Padmakumar and He He. North American Chapter of the Association for Computational Linguistics (NAACL), 2022. [bib] [code] - Meta-learning via Language Model In-context Tuning.
Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis and He He. Association for Computational Linguistics (ACL), 2022. [bib] [code] - Faithful or Extractive? On Mitigating the Faithfulness-Abstractiveness Trade-off in Abstractive Summarization.
Faisal Ladhak, Esin Durmus, He He, Claire Cardie and Kathleen McKeown. Association for Computational Linguistics (ACL), 2022. [bib] - An Investigation of the (In)effectiveness of Counterfactually Augmented Data.
Nitish Joshi and He He. Association for Computational Linguistics (ACL), 2022. [bib] [code]
2021
- {IRM} - When It Works and When It Doesn't: A Test Case of Natural Language Inference.
Yana Dranker, He He and Yonatan Belinkov. Neural Information Processing Systems (NeurIPS), 2021. [bib] [code] - Types of Out-of-Distribution Texts and How to Detect Them.
Udit Arora, William Huang and He He. Empirical Methods in Natural Language Processing (EMNLP), 2021. [bib] [code] - Unsupervised Extractive Summarization with Pointwise Mutual Information.
Vishakh Padmakumar and He He. The European Chapter of the Association for Computational Linguistics (EACL), 2021. [bib] [code] - Text Generation by Learning from Demonstrations.
Richard Yuanzhe Pang and He He. International Conference on Learning Representations (ICLR), 2021. [bib] [code]
2020
- An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language Models.
Lifu Tu, Garima Lalwani, Spandana Gella and He He. Transaction of Association for Computational Linguistics (TACL), 2020. [bib] [code] - FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization.
Esin Durmus, He He and Mona Diab. Association for Computational Linguistics (ACL), 2020. [bib] [code] [talk] - GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing.
Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng and Yi Zhu. Journal of Machine Learning Research (JMLR), 2020. [bib] [project]
2019
- Unlearn Dataset Bias for Natural Language Inference by Fitting the Residual.
He He, Sheng Zha and Haohan Wang. EMNLP Workshop on DeepLo, 2019. [bib] [code] - Pun Generation with Surprise.
He He*, Nanyun Peng* and Percy Liang. North American Chapter of the Association for Computational Linguistics (NAACL), 2019. [bib] [code] [codalab] - Quizbowl: The Case for Incremental Question Answering.
Petro Rodriguez, Shi Feng, Mohit Iyyer, He He and Jordan Boyd-Graber. arXiv:1904.04792 preprint, 2019. [bib] - A Dynamic Strategy Coach for Effective Negotiation.
Yiheng Zhou, He He, Alan Black and Yulia Tsvetkov. Special Interest Group on Discource and Dialogue (SigDial), 2019. [bib] [code]
2018
- Decoupling Strategy and Generation in Negotiation Dialogues.
He He, Derek Chen, Anusha Balakrishnan and Percy Liang. Empirical Methods in Natural Language Processing (EMNLP), 2018. [bib] [project] - QuAC: Question Answering in Context.
Eunsol Choi*, He He*, Mohit Iyyer*, Mark Yatskar*, Wen-tau Yih, Yejin Choi, Percy Liang and Luke Zettlemoyer. Empirical Methods in Natural Language Processing (EMNLP), 2018. [bib] [project] - Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context.
Urvashi Khandelwal, He He, Peng Qi and Dan Jurafsky. Association for Computational Linguistics (ACL), 2018. [bib] [code] - Delete, Retrieve, Generate: a Simple Approach to Sentiment and Style Transfer.
Juncen Li, Robin Jia, He He and Percy Liang. North American Chapter of the Association for Computational Linguistics (NAACL), 2018. [bib] [code]
2017
- Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings.
He He, Anusha Balakrishnan, Mihail Eric and Percy Liang. Association for Computational Linguistics (ACL), 2017. [bib] [project]
2016
- Credit Assignment Compiler for Joint Prediction.
Kai-Wei Chang, He He, Hal Daumé III, John Langford and Stéphane Ross. Neural Information Processing Systems (NeurIPS), 2016. [bib] [code] - Opponent Modeling in Deep Reinforcement Learning.
He He, Jordan Boyd-Graber, Kevin Kwok and Hal Daumé III. International Conference on Machine Learning (ICML), 2016. [bib] [code] [data] - Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation.
He He, Jordan Boyd-Graber and Hal Daumé III. North American Chapter of the Association for Computational Linguistics (NAACL), 2016. [bib] [code] - Object Detection in 20 Questions.
Xi Chen, He He and Larry Davis. Winter Conference on Applications of Computer Vision (WACV), 2016. [bib]
2015
- Active Information Acquisition.
He He, Paul Mineiro and Nikos Karampatziakis. ICML Workshop on Machine Learning From and For Adaptive User Technologies: From Active Learning & Experimentation to Optimization & Personalization, 2015. [bib] [poster] - Interactive Incremental Question Answering. (Outstanding Demonstration Award)
Jordan Boyd-Graber, Mohit Iyyer, He He and Hal Daumé III. Neural Information Processing Systems (NeurIPS) demo, 2015. - Syntax-based Rewriting for Simultaneous Machine Translation.
He He, Alvin Grissom II, John Morgan, Jordan Boyd-Graber and Hal Daumé III. Empirical Methods in Natural Language Processing (EMNLP), 2015. [bib] [code] [slides] - Learning to Search for Dependencies.
Kai-Wei Chang, He He, Hal Daumé III and John Langford. arXiv:1503.05615 preprint, 2015. [bib] [code] - Crowdsourcing with Multi-Dimensional Trust.
Xiangyang Liu, He He and John Baras. International Conference on Information Fusion (Fusion), 2015. [bib] - Trust-Aware Optimal Crowdsourcing With Budget Constraint.
Xiangyang Liu, He He and John Baras. International Conference on Communications (ICC), 2015. [bib]
2014
- Temporal Supervised Learning for Inferring a Dialog Policy from Example Conversations.
Lihong Li, He He and Jason D. Williams. Spoken Lanugage Technology Workshop (SLT), 2014. [bib] - Learning to Search in Branch and Bound Algorithms.
He He, Hal Daumé III and Jason Eisner. Neural Information Processing Systems (NeurIPS), 2014. [bib] [code] [poster] - Don't Until the Final Verb Wait: Reinforcement Learning for Simultaneous Machine Translation.
Alvin Grissom II, He He, John Morgan, Jordan Boyd-Graber and Hal Daumé III. Empirical Methods in Natural Language Processing (EMNLP), 2014. [bib] [talk]
2013
- Dynamic Feature Selection for Dependency Parsing.
He He, Hal Daumé III and Jason Eisner. Empirical Methods in Natural Language Processing (EMNLP), 2013. [bib] [slides] [talk]
2012
- Imitation Learning by Coaching.
He He, Hal Daumé III and Jason Eisner. Neural Information Processing Systems (NeurIPS), 2012. [bib] [poster] - Besting the Quiz Master: Crowdsourcing Incremental Classification Games.
Jordan Boyd-Graber, Brianna Satinoff, He He and Hal Daumé III. Empirical Methods in Natural Language Processing (EMNLP), 2012. [bib] - Cost-sensitive dynamic feature selection.
He He, Hal Daumé III and Jason Eisner. ICML Workshop on Inferning, 2012. [bib] [slides] [poster]
2011
- Single Image Super-resolution using Gaussian Process Regression.
He He and Wan-Chi Siu. Computer Vision and Pattern Recognition (CVPR), 2011. [bib] [code] [slides]
2010
- Rare Class classification with SVM.
He He and Ali Ghodsi. International Conference on Pattern Recognition (ICPR), 2010. [bib] [code] [poster]