He He

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 83

Top Venues

University of Maryland, College Park, MD, USA (PHD)

Education History

University of Maryland, College Park, MD, USA

PHD

Publications

Guande Wu, Chen Zhao, Cláudio T. Silva, He He
Your Co-Workers Matter: Evaluating Collaborative Capabilities of Language Models in Blocks World. CoRR (2024)
Richard Yuanzhe Pang, Stephen Roller, Kyunghyun Cho, He He, Jason Weston
Leveraging Implicit Feedback from Deployment Data in Dialogue. EACL (2) (2024)
Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, He He, Sainbayar Sukhbaatar, Jason Weston
Iterative Reasoning Preference Optimization. CoRR (2024)
Jane Pan, He He, Samuel R. Bowman, Shi Feng
Spontaneous Reward Hacking in Iterative Self-Refinement. CoRR (2024)
Yanda Chen, Chen Zhao, Zhou Yu, Kathleen R. McKeown, He He
Parallel Structures in Pre-training Data Yield In-Context Learning. ACL (1) (2024)
Aahlad Manas Puli, Nitish Joshi, Yoav Wald, He He, Rajesh Ranganath
Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation. Trans. Mach. Learn. Res. 2024 (2024)
Sonia Castelo, João Rulff, Erin McGowan, Bea Steers, Guande Wu, Shaoyu Chen, Irán R. Román, Roque Lopez, Ethan Brewer, Chen Zhao, Jing Qian, Kyunghyun Cho, He He, Qi Sun, Huy T. Vo, Juan Pablo Bello, Michael Krone, Cláudio T. Silva
: Visualization of AI-Assisted Task Guidance in AR. IEEE Trans. Vis. Comput. Graph. 30 (1) (2024)
Nitish Joshi, Abulhair Saparov, Yixin Wang, He He
LLMs Are Prone to Fallacies in Causal Inference. CoRR (2024)
Vishakh Padmakumar, He He
Does Writing with Language Models Reduce Content Diversity? ICLR (2024)
Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, José Hernández-Orallo, Lewis Hammond, Eric J. Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Zhang, Ruiqi Zhong, Seán Ó hÉigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Yoshua Bengio, Danqi Chen, Samuel Albanie, Tegan Maharaj, Jakob N. Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger
Foundational Challenges in Assuring Alignment and Safety of Large Language Models. CoRR (2024)
Yanda Chen, Chandan Singh, Xiaodong Liu, Simiao Zuo, Bin Yu, He He, Jianfeng Gao
Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning. CoRR (2024)
Nicholas Lourie, Kyunghyun Cho, He He
Show Your Work with Confidence: Confidence Bands for Tuning Curves. NAACL-HLT (2024)
Guande Wu, Chen Zhao, Cláudio T. Silva, He He
Your Co-Workers Matter: Evaluating Collaborative Capabilities of Language Models in Blocks World. ACL (Findings) (2024)
Yanda Chen, Chen Zhao, Zhou Yu, Kathleen R. McKeown, He He
Parallel Structures in Pre-training Data Yield In-Context Learning. CoRR (2024)
Sonia Castelo, João Rulff, Erin McGowan, Bea Steers, Guande Wu, Shaoyu Chen, Irán R. Román, Roque Lopez, Ethan Brewer, Chen Zhao, Jing Qian, Kyunghyun Cho, He He, Qi Sun, Huy T. Vo, Juan Pablo Bello, Michael Krone, Cláudio T. Silva
ARGUS: Visualization of AI-Assisted Task Guidance in AR. CoRR (2023)
Chenglei Si, Dan Friedman, Nitish Joshi, Shi Feng, Danqi Chen, He He
Measuring Inductive Biases of In-Context Learning with Underspecified Demonstrations. ACL (1) (2023)
Nicholas Lourie, Kyunghyun Cho, He He
Show Your Work with Confidence: Confidence Bands for Tuning Curves. CoRR (2023)
Chenghao Yang, Fan Yin, He He, Kai-Wei Chang, Xiaofei Ma, Bing Xiang
Efficient Shapley Values Estimation by Amortization for Text Classification. CoRR (2023)
Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Seyed Mehran Kazemi, Najoung Kim, He He
Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples. CoRR (2023)
Chenglei Si, Dan Friedman, Nitish Joshi, Shi Feng, Danqi Chen, He He
Measuring Inductive Biases of In-Context Learning with Underspecified Demonstrations. CoRR (2023)
Abulhair Saparov, He He
Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought. ICLR (2023)
Richard Yuanzhe Pang, Stephen Roller, Kyunghyun Cho, He He, Jason Weston
Leveraging Implicit Feedback from Deployment Data in Dialogue. CoRR (2023)
Vishakh Padmakumar, Richard Yuanzhe Pang, He He, Ankur P. Parikh
Extrapolative Controlled Sequence Generation via Iterative Refinement. CoRR (2023)
Chenghao Yang, Fan Yin, He He, Kai-Wei Chang, Xiaofei Ma, Bing Xiang
Efficient Shapley Values Estimation by Amortization for Text Classification. ACL (1) (2023)
Nitish Joshi, Javier Rando, Abulhair Saparov, Najoung Kim, He He
Personas as a Way to Model Truthfulness in Language Models. CoRR (2023)
Yanda Chen, Chen Zhao, Zhou Yu, Kathleen R. McKeown, He He
On the Relation between Sensitivity and Accuracy in In-Context Learning. EMNLP (Findings) (2023)
Richard Yuanzhe Pang, Vishakh Padmakumar, Thibault Sellam, Ankur P. Parikh, He He
Reward Gaming in Conditional Text Generation. ACL (1) (2023)
Vishakh Padmakumar, Richard Yuanzhe Pang, He He, Ankur P. Parikh
Extrapolative Controlled Sequence Generation via Iterative Refinement. ICML (2023)
Vishakh Padmakumar, He He
Does Writing with Language Models Reduce Content Diversity? CoRR (2023)
Yanda Chen, Ruiqi Zhong, Narutatsu Ri, Chen Zhao, He He, Jacob Steinhardt, Zhou Yu, Kathleen R. McKeown
Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations. CoRR (2023)
Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Mehran Kazemi, Najoung Kim, He He
Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples. NeurIPS (2023)
Aahlad Manas Puli, Nitish Joshi, He He, Rajesh Ranganath
Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation. CoRR (2022)
Nitish Joshi, He He
An Investigation of the (In)effectiveness of Counterfactually Augmented Data. ACL (1) (2022)
Faisal Ladhak, Esin Durmus, He He, Claire Cardie, Kathleen R. McKeown
Faithful or Extractive? On Mitigating the Faithfulness-Abstractiveness Trade-off in Abstractive Summarization. ACL (1) (2022)
Richard Yuanzhe Pang, Vishakh Padmakumar, Thibault Sellam, Ankur P. Parikh, He He
Reward Gaming in Conditional Text Generation. CoRR (2022)
Nitish Joshi, Xiang Pan, He He
Are All Spurious Features in Natural Language Alike? An Analysis through a Causal Lens. EMNLP (2022)
Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He
Meta-learning via Language Model In-context Tuning. ACL (1) (2022)
Tuhin Chakrabarty, Vishakh Padmakumar, He He
Help me write a Poem - Instruction Tuning as a Vehicle for Collaborative Poetry Writing. EMNLP (2022)
Vishakh Padmakumar, He He
Machine-in-the-Loop Rewriting for Creative Image Captioning. NAACL-HLT (2022)
Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. NAACL-HLT (2022)
Yanda Chen, Chen Zhao, Zhou Yu, Kathleen R. McKeown, He He
On the Relation between Sensitivity and Accuracy in In-context Learning. CoRR (2022)
Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, Nikita Nangia, Jason Phang, Angelica Chen, Vishakh Padmakumar, Johnny Ma, Jana Thompson, He He, Samuel R. Bowman
QuALITY: Question Answering with Long Input Texts, Yes! NAACL-HLT (2022)
Tuhin Chakrabarty, Vishakh Padmakumar, He He
Help me write a poem: Instruction Tuning as a Vehicle for Collaborative Poetry Writing. CoRR (2022)
Nitish Joshi, Xiang Pan, He He
Are All Spurious Features in Natural Language Alike? An Analysis through a Causal Lens. CoRR (2022)
Tianshu Wang, Faisal Ladhak, Esin Durmus, He He
Improving Faithfulness by Augmenting Negative Summaries from Fake Documents. EMNLP (2022)
Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. CoRR (2022)
Yana Dranker, He He, Yonatan Belinkov
IRM - when it works and when it doesn't: A test case of natural language inference. NeurIPS (2021)
Faisal Ladhak, Esin Durmus, He He, Claire Cardie, Kathleen R. McKeown
Faithful or Extractive? On Mitigating the Faithfulness-Abstractiveness Trade-off in Abstractive Summarization. CoRR (2021)
Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, Nikita Nangia, Jason Phang, Angelica Chen, Vishakh Padmakumar, Johnny Ma, Jana Thompson, He He, Samuel R. Bowman
QuALITY: Question Answering with Long Input Texts, Yes! CoRR (2021)
Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He
Meta-learning via Language Model In-context Tuning. CoRR (2021)
Richard Yuanzhe Pang, He He
Text Generation by Learning from Demonstrations. ICLR (2021)
Richard Yuanzhe Pang, He He, Kyunghyun Cho
Amortized Noisy Channel Neural Machine Translation. CoRR (2021)
Lifu Tu, Garima Lalwani, Spandana Gella, He He
An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language Models. CoRR (2020)
Richard Yuanzhe Pang, He He
Text Generation by Learning from Off-Policy Demonstrations. CoRR (2020)
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, Yi Zhu
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. J. Mach. Learn. Res. 21 (2020)
Lifu Tu, Garima Lalwani, Spandana Gella, He He
An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language Models. Trans. Assoc. Comput. Linguistics 8 (2020)
Esin Durmus, He He, Mona Diab
FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization. CoRR (2020)
Esin Durmus, He He, Mona Diab
FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization. ACL (2020)
He He, Nanyun Peng, Percy Liang
Pun Generation with Surprise. NAACL-HLT (1) (2019)
Pedro Rodriguez, Shi Feng, Mohit Iyyer, He He, Jordan L. Boyd-Graber
Quizbowl: The Case for Incremental Question Answering. CoRR (2019)
Yiheng Zhou, He He, Alan W. Black, Yulia Tsvetkov
A Dynamic Strategy Coach for Effective Negotiation. SIGdial (2019)
Yiheng Zhou, He He, Alan W. Black, Yulia Tsvetkov
A Dynamic Strategy Coach for Effective Negotiation. CoRR (2019)
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
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. CoRR (2019)
He He, Sheng Zha, Haohan Wang
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual. CoRR (2019)
He He, Sheng Zha, Haohan Wang
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual. DeepLo@EMNLP-IJCNLP (2019)
He He, Nanyun Peng, Percy Liang
Pun Generation with Surprise. CoRR (2019)
Haibin Lin, Xingjian Shi, Leonard Lausen, Aston Zhang, He He, Sheng Zha, Alexander J. Smola
Dive into Deep Learning for Natural Language Processing. EMNLP/IJCNLP (2) (2019)
Juncen Li, Robin Jia, He He, Percy Liang
Delete, Retrieve, Generate: a Simple Approach to Sentiment and Style Transfer. NAACL-HLT (2018)
He He, Derek Chen, Anusha Balakrishnan, Percy Liang
Decoupling Strategy and Generation in Negotiation Dialogues. EMNLP (2018)
He He, Derek Chen, Anusha Balakrishnan, Percy Liang
Decoupling Strategy and Generation in Negotiation Dialogues. CoRR (2018)
Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang, Luke Zettlemoyer
QuAC : Question Answering in Context. CoRR (2018)
Urvashi Khandelwal, He He, Peng Qi, Dan Jurafsky
Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context. ACL (1) (2018)
Urvashi Khandelwal, He He, Peng Qi, Dan Jurafsky
Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context. CoRR (2018)
Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang, Luke Zettlemoyer
QuAC: Question Answering in Context. EMNLP (2018)
Juncen Li, Robin Jia, He He, Percy Liang
Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer. CoRR (2018)
He He, Anusha Balakrishnan, Mihail Eric, Percy Liang
Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings. ACL (1) (2017)
He He, Anusha Balakrishnan, Mihail Eric, Percy Liang
Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings. CoRR (2017)
He He, Paul Mineiro, Nikos Karampatziakis
Active Information Acquisition. CoRR (2016)
He He, Jordan L. Boyd-Graber
Opponent Modeling in Deep Reinforcement Learning. ICML (2016)
He He, Jordan L. Boyd-Graber, Kevin Kwok, Hal Daumé III
Opponent Modeling in Deep Reinforcement Learning. CoRR (2016)
Kai-Wei Chang, He He, Stéphane Ross, Hal Daumé III, John Langford
A Credit Assignment Compiler for Joint Prediction. NIPS (2016)
Xi (Stephen) Chen, He He, Larry S. Davis
Object detection in 20 questions. WACV (2016)
He He, Jordan L. Boyd-Graber, Hal Daumé III
Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation. HLT-NAACL (2016)
He He, Alvin Grissom II, John Morgan, Jordan L. Boyd-Graber, Hal Daumé III
Syntax-based Rewriting for Simultaneous Machine Translation. EMNLP (2015)
Kai-Wei Chang, He He, Hal Daumé III, John Langford
Learning to Search for Dependencies. CoRR (2015)
Hal Daumé III, John Langford, Kai-Wei Chang, He He, Sudha Rao
Hands-on Learning to Search for Structured Prediction. HLT-NAACL (2015)
Xiangyang Liu, He He, John S. Baras
Crowdsourcing with multi-dimensional trust. FUSION (2015)
Xiangyang Liu, He He, John S. Baras
Trust-aware optimal crowdsourcing with budget constraint. ICC (2015)
Lihong Li, He He, Jason D. Williams
Temporal supervised learning for inferring a dialog policy from example conversations. SLT (2014)
He He, Hal Daumé III, Jason Eisner
Learning to Search in Branch and Bound Algorithms. NIPS (2014)
Alvin Grissom II, He He, Jordan L. Boyd-Graber, John Morgan, Hal Daumé III
Don't Until the Final Verb Wait: Reinforcement Learning for Simultaneous Machine Translation. EMNLP (2014)
He He, Hal Daumé III, Jason Eisner
Dynamic Feature Selection for Dependency Parsing. EMNLP (2013)
He He, Hal Daumé III, Jason Eisner
Imitation Learning by Coaching. NIPS (2012)
Jordan L. Boyd-Graber, Brianna Satinoff, He He, Hal Daumé III
Besting the Quiz Master: Crowdsourcing Incremental Classification Games. EMNLP-CoNLL (2012)
He He, Wan-Chi Siu
Single image super-resolution using Gaussian process regression. CVPR (2011)
He He, Ali Ghodsi
Rare Class Classification by Support Vector Machine. ICPR (2010)

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Publication Activity (10 Years)

Top Topics

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He He