He He - RankMe

131 papers A* 25A 2B 3C 1Journal 65Unranked 31

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Factuality on Demand: Controlling the Factuality-Informativeness Trade-off in Text Generation. CoRR Ziwei Gong, Yanda Chen, Julia Hirschberg, Chen Zhao, He He, Zhou Yu, Kathleen R. McKeown
2025	A*	`conf`	Adaptive Deployment of Untrusted LLMs Reduces Distributed Threats. ICLR Jiaxin Wen, Vivek Hebbar, Caleb Larson, Aryan Bhatt, Ansh Radhakrishnan, Mrinank Sharma, Henry Sleight, Shi Feng, He He, Ethan Perez, Buck Shlegeris, Akbir Khan
2025	J	`jnl`	Beyond Memorization: Mapping the Originality-Quality Frontier of Language Models. CoRR Vishakh Padmakumar, Chen Yueh-Han, Jane Pan, Valerie Chen, He He
2025	J	`jnl`	Hyperparameter Loss Surfaces Are Simple Near their Optima. CoRR Nicholas Lourie, He He, Kyunghyun Cho
2025	J	`jnl`	Is It Thinking or Cheating? Detecting Implicit Reward Hacking by Measuring Reasoning Effort. CoRR Xinpeng Wang, Nitish Joshi, Barbara Plank, Rico Angell, He He
2025	A*	`conf`	Language Models Learn to Mislead Humans via RLHF. ICLR Jiaxin Wen, Ruiqi Zhong, Akbir Khan, Ethan Perez, Jacob Steinhardt, Minlie Huang, Samuel R. Bowman, He He, Shi Feng
2025	J	`jnl`	Monitoring Decomposition Attacks in LLMs with Lightweight Sequential Monitors. CoRR Chen Yueh-Han, Nitish Joshi, Yulin Chen, Maksym Andriushchenko, Rico Angell, He He
2025	J	`jnl`	Reasoning Models Know When They're Right: Probing Hidden States for Self-Verification. CoRR Anqi Zhang, Yulin Chen, Jane Pan, Chen Zhao, Aurojit Panda, Jinyang Li, He He
2025	B	`conf`	Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning. COLING Yanda Chen, Chandan Singh, Xiaodong Liu, Simiao Zuo, Bin Yu, He He, Jianfeng Gao
2025	A*	`conf`	Transformers Struggle to Learn to Search. ICLR Abulhair Saparov, Srushti Ajay Pawar, Shreyas Pimpalgaonkar, Nitish Joshi, Richard Yuanzhe Pang, Vishakh Padmakumar, Mehran Kazemi, Najoung Kim, He He
2025	J	`jnl`	Unsupervised Elicitation of Language Models. CoRR Jiaxin Wen, Zachary Ankner, Arushi Somani, Peter Hase, Samuel Marks, Jacob Goldman-Wetzler, Linda Petrini, Henry Sleight, Collin Burns, He He, Shi Feng, Ethan Perez, Jan Leike
2025	—	`conf`	When Benchmarks Talk: Re-Evaluating Code LLMs with Interactive Feedback. ACL (Findings) Jane Pan, Ryan Shar, Jacob Pfau, Ameet Talwalkar, He He, Valerie Chen
2025	J	`jnl`	When Benchmarks Talk: Re-Evaluating Code LLMs with Interactive Feedback. CoRR Jane Pan, Ryan Shar, Jacob Pfau, Ameet Talwalkar, He He, Valerie Chen
2024	J	`jnl`	: Visualization of AI-Assisted Task Guidance in AR. IEEE Trans. Vis. Comput. Graph. 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
2024	J	`jnl`	Adaptive Deployment of Untrusted LLMs Reduces Distributed Threats. CoRR Jiaxin Wen, Vivek Hebbar, Caleb Larson, Aryan Bhatt, Ansh Radhakrishnan, Mrinank Sharma, Henry Sleight, Shi Feng, He He, Ethan Perez, Buck Shlegeris, Akbir Khan
2024	J	`jnl`	Beyond the Binary: Capturing Diverse Preferences With Reward Regularization. CoRR Vishakh Padmakumar, Chuanyang Jin, Hannah Rose Kirk, He He
2024	A*	`conf`	Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations. ICML Yanda Chen, Ruiqi Zhong, Narutatsu Ri, Chen Zhao, He He, Jacob Steinhardt, Zhou Yu, Kathleen R. McKeown
2024	A*	`conf`	Does Writing with Language Models Reduce Content Diversity? ICLR Vishakh Padmakumar, He He
2024	J	`jnl`	Foundational Challenges in Assuring Alignment and Safety of Large Language Models. CoRR 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 C. 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
2024	J	`jnl`	Foundational Challenges in Assuring Alignment and Safety of Large Language Models. Trans. Mach. Learn. Res. 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 Chenyu Zhang, Ruiqi Zhong, Seán Ó hÉigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Aleksandar Petrov, Christian Schröder de Witt, Sumeet Ramesh Motwani, Yoshua Bengio, Danqi Chen, Philip Torr, Samuel Albanie, Tegan Maharaj, Jakob Nicolaus Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger
2024	A*	`conf`	Iterative Reasoning Preference Optimization. NeurIPS Richard Yuanzhe Pang, Weizhe Yuan, He He, Kyunghyun Cho, Sainbayar Sukhbaatar, Jason Weston
2024	J	`jnl`	Iterative Reasoning Preference Optimization. CoRR Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, He He, Sainbayar Sukhbaatar, Jason Weston
2024	A*	`conf`	LLMs Are Prone to Fallacies in Causal Inference. EMNLP Nitish Joshi, Abulhair Saparov, Yixin Wang, He He
2024	J	`jnl`	LLMs Are Prone to Fallacies in Causal Inference. CoRR Nitish Joshi, Abulhair Saparov, Yixin Wang, He He
2024	J	`jnl`	Language Models Learn to Mislead Humans via RLHF. CoRR Jiaxin Wen, Ruiqi Zhong, Akbir Khan, Ethan Perez, Jacob Steinhardt, Minlie Huang, Samuel R. Bowman, He He, Shi Feng
2024	—	`conf`	Leveraging Implicit Feedback from Deployment Data in Dialogue. EACL (2) Richard Yuanzhe Pang, Stephen Roller, Kyunghyun Cho, He He, Jason Weston
2024	J	`jnl`	Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation. Trans. Mach. Learn. Res. Aahlad Manas Puli, Nitish Joshi, Yoav Wald, He He, Rajesh Ranganath
2024	—	`conf`	Parallel Structures in Pre-training Data Yield In-Context Learning. ACL (1) Yanda Chen, Chen Zhao, Zhou Yu, Kathleen R. McKeown, He He
2024	J	`jnl`	Parallel Structures in Pre-training Data Yield In-Context Learning. CoRR Yanda Chen, Chen Zhao, Zhou Yu, Kathleen R. McKeown, He He
2024	A*	`conf`	Personas as a Way to Model Truthfulness in Language Models. EMNLP Nitish Joshi, Javier Rando, Abulhair Saparov, Najoung Kim, He He
2024	—	`conf`	Show Your Work with Confidence: Confidence Bands for Tuning Curves. NAACL-HLT Nicholas Lourie, Kyunghyun Cho, He He
2024	J	`jnl`	Spontaneous Reward Hacking in Iterative Self-Refinement. CoRR Jane Pan, He He, Samuel R. Bowman, Shi Feng
2024	A*	`conf`	The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models. NeurIPS Hannah Rose Kirk, Alexander Whitefield, Paul Röttger, Andrew M. Bean, Katerina Margatina, Rafael Mosquera Gómez, Juan Ciro, Max Bartolo, Adina Williams, He He, Bertie Vidgen, Scott Hale
2024	J	`jnl`	The PRISM Alignment Project: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models. CoRR Hannah Rose Kirk, Alexander Whitefield, Paul Röttger, Andrew M. Bean, Katerina Margatina, Juan Ciro, Rafael Mosquera, Max Bartolo, Adina Williams, He He, Bertie Vidgen, Scott A. Hale
2024	J	`jnl`	Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning. CoRR Yanda Chen, Chandan Singh, Xiaodong Liu, Simiao Zuo, Bin Yu, He He, Jianfeng Gao
2024	J	`jnl`	Transformers Struggle to Learn to Search. CoRR Abulhair Saparov, Srushti Pawar, Shreyas Pimpalgaonkar, Nitish Joshi, Richard Yuanzhe Pang, Vishakh Padmakumar, Seyed Mehran Kazemi, Najoung Kim, He He
2024	—	`conf`	Your Co-Workers Matter: Evaluating Collaborative Capabilities of Language Models in Blocks World. ACL (Findings) Guande Wu, Chen Zhao, Cláudio T. Silva, He He
2024	J	`jnl`	Your Co-Workers Matter: Evaluating Collaborative Capabilities of Language Models in Blocks World. CoRR Guande Wu, Chen Zhao, Cláudio T. Silva, He He
2023	J	`jnl`	ARGUS: Visualization of AI-Assisted Task Guidance in AR. CoRR 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
2023	—	`conf`	Creative Natural Language Generation. EMNLP (Tutorial Abstracts) Tuhin Chakrabarty, Vishakh Padmakumar, He He, Nanyun Peng
2023	J	`jnl`	Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations. CoRR Yanda Chen, Ruiqi Zhong, Narutatsu Ri, Chen Zhao, He He, Jacob Steinhardt, Zhou Yu, Kathleen R. McKeown
2023	J	`jnl`	Does Writing with Language Models Reduce Content Diversity? CoRR Vishakh Padmakumar, He He
2023	—	`conf`	Efficient Shapley Values Estimation by Amortization for Text Classification. ACL (1) Chenghao Yang, Fan Yin, He He, Kai-Wei Chang, Xiaofei Ma, Bing Xiang
2023	J	`jnl`	Efficient Shapley Values Estimation by Amortization for Text Classification. CoRR Chenghao Yang, Fan Yin, He He, Kai-Wei Chang, Xiaofei Ma, Bing Xiang
2023	A*	`conf`	Extrapolative Controlled Sequence Generation via Iterative Refinement. ICML Vishakh Padmakumar, Richard Yuanzhe Pang, He He, Ankur P. Parikh
2023	J	`jnl`	Extrapolative Controlled Sequence Generation via Iterative Refinement. CoRR Vishakh Padmakumar, Richard Yuanzhe Pang, He He, Ankur P. Parikh
2023	A*	`conf`	Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought. ICLR Abulhair Saparov, He He
2023	J	`jnl`	Leveraging Implicit Feedback from Deployment Data in Dialogue. CoRR Richard Yuanzhe Pang, Stephen Roller, Kyunghyun Cho, He He, Jason Weston
2023	—	`conf`	Measuring Inductive Biases of In-Context Learning with Underspecified Demonstrations. ACL (1) Chenglei Si, Dan Friedman, Nitish Joshi, Shi Feng, Danqi Chen, He He
2023	J	`jnl`	Measuring Inductive Biases of In-Context Learning with Underspecified Demonstrations. CoRR Chenglei Si, Dan Friedman, Nitish Joshi, Shi Feng, Danqi Chen, He He
2023	—	`conf`	On the Relation between Sensitivity and Accuracy in In-Context Learning. EMNLP (Findings) Yanda Chen, Chen Zhao, Zhou Yu, Kathleen R. McKeown, He He
2023	J	`jnl`	Personas as a Way to Model Truthfulness in Language Models. CoRR Nitish Joshi, Javier Rando, Abulhair Saparov, Najoung Kim, He He
2023	—	`conf`	Reward Gaming in Conditional Text Generation. ACL (1) Richard Yuanzhe Pang, Vishakh Padmakumar, Thibault Sellam, Ankur P. Parikh, He He
2023	J	`jnl`	Show Your Work with Confidence: Confidence Bands for Tuning Curves. CoRR Nicholas Lourie, Kyunghyun Cho, He He
2023	A*	`conf`	Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples. NeurIPS Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Mehran Kazemi, Najoung Kim, He He
2023	J	`jnl`	Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples. CoRR Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Seyed Mehran Kazemi, Najoung Kim, He He
2022	—	`conf`	An Investigation of the (In)effectiveness of Counterfactually Augmented Data. ACL (1) Nitish Joshi, He He
2022	A*	`conf`	Are All Spurious Features in Natural Language Alike? An Analysis through a Causal Lens. EMNLP Nitish Joshi, Xiang Pan, He He
2022	J	`jnl`	Are All Spurious Features in Natural Language Alike? An Analysis through a Causal Lens. CoRR Nitish Joshi, Xiang Pan, He He
2022	—	`conf`	Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. NAACL-HLT Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis
2022	J	`jnl`	Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. CoRR Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis
2022	—	`conf`	Faithful or Extractive? On Mitigating the Faithfulness-Abstractiveness Trade-off in Abstractive Summarization. ACL (1) Faisal Ladhak, Esin Durmus, He He, Claire Cardie, Kathleen R. McKeown
2022	A*	`conf`	Help me write a Poem - Instruction Tuning as a Vehicle for Collaborative Poetry Writing. EMNLP Tuhin Chakrabarty, Vishakh Padmakumar, He He
2022	J	`jnl`	Help me write a poem: Instruction Tuning as a Vehicle for Collaborative Poetry Writing. CoRR Tuhin Chakrabarty, Vishakh Padmakumar, He He
2022	A*	`conf`	Improving Faithfulness by Augmenting Negative Summaries from Fake Documents. EMNLP Tianshu Wang, Faisal Ladhak, Esin Durmus, He He
2022	J	`jnl`	Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought. CoRR Abulhair Saparov, He He
2022	—	`conf`	Machine-in-the-Loop Rewriting for Creative Image Captioning. NAACL-HLT Vishakh Padmakumar, He He
2022	—	`conf`	Meta-learning via Language Model In-context Tuning. ACL (1) Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He
2022	J	`jnl`	Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation. CoRR Aahlad Manas Puli, Nitish Joshi, He He, Rajesh Ranganath
2022	J	`jnl`	On the Relation between Sensitivity and Accuracy in In-context Learning. CoRR Yanda Chen, Chen Zhao, Zhou Yu, Kathleen R. McKeown, He He
2022	—	`ed.`	Proceedings of the 7th Workshop on Representation Learning for NLP, RepL4NLP@ACL 2022, Dublin, Ireland, May 26, 2022 RepL4NLP@ACL Spandana Gella, He He, Bodhisattwa Prasad Majumder, Burcu Can, Eleonora Giunchiglia, Samuel Cahyawijaya, Sewon Min, Maximilian Mozes, Xiang Lorraine Li, Isabelle Augenstein, Anna Rogers, Kyunghyun Cho, Edward Grefenstette, Laura Rimell, Chris Dyer
2022	—	`conf`	QuALITY: Question Answering with Long Input Texts, Yes! NAACL-HLT Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, Nikita Nangia, Jason Phang, Angelica Chen, Vishakh Padmakumar, Johnny Ma, Jana Thompson, He He, Samuel R. Bowman
2022	J	`jnl`	Reward Gaming in Conditional Text Generation. CoRR Richard Yuanzhe Pang, Vishakh Padmakumar, Thibault Sellam, Ankur P. Parikh, He He
2021	J	`jnl`	Amortized Noisy Channel Neural Machine Translation. CoRR Richard Yuanzhe Pang, He He, Kyunghyun Cho
2021	J	`jnl`	An Investigation of the (In)effectiveness of Counterfactually Augmented Data. CoRR Nitish Joshi, He He
2021	J	`jnl`	Faithful or Extractive? On Mitigating the Faithfulness-Abstractiveness Trade-off in Abstractive Summarization. CoRR Faisal Ladhak, Esin Durmus, He He, Claire Cardie, Kathleen R. McKeown
2021	A*	`conf`	IRM - when it works and when it doesn't: A test case of natural language inference. NeurIPS Yana Dranker, He He, Yonatan Belinkov
2021	J	`jnl`	Machine-in-the-Loop Rewriting for Creative Image Captioning. CoRR Vishakh Padmakumar, He He
2021	J	`jnl`	Meta-learning via Language Model In-context Tuning. CoRR Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He
2021	—	`ed.`	Proceedings of the 1st Workshop on Document-grounded Dialogue and Conversational Question Answering, DialDoc@ACL-IJCNLP 2021, Online, August 5, 2021 DialDoc@ACL-IJCNLP Song Feng, Siva Reddy, Malihe Alikhani, He He, Yangfeng Ji, Mohit Iyyer, Zhou Yu
2021	J	`jnl`	QuALITY: Question Answering with Long Input Texts, Yes! CoRR Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, Nikita Nangia, Jason Phang, Angelica Chen, Vishakh Padmakumar, Johnny Ma, Jana Thompson, He He, Samuel R. Bowman
2021	—	`conf`	Robustness and Adversarial Examples in Natural Language Processing. EMNLP (Tutorial Abstracts) Kai-Wei Chang, He He, Robin Jia, Sameer Singh
2021	A*	`conf`	Text Generation by Learning from Demonstrations. ICLR Richard Yuanzhe Pang, He He
2021	A	`conf`	Unsupervised Extractive Summarization using Pointwise Mutual Information. EACL Vishakh Padmakumar, He He
2021	J	`jnl`	Unsupervised Extractive Summarization using Pointwise Mutual Information. CoRR Vishakh Padmakumar, He He
2020	J	`jnl`	An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language Models. CoRR Lifu Tu, Garima Lalwani, Spandana Gella, He He
2020	J	`jnl`	An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language Models. Trans. Assoc. Comput. Linguistics Lifu Tu, Garima Lalwani, Spandana Gella, He He
2020	A*	`conf`	FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization. ACL Esin Durmus, He He, Mona T. Diab
2020	J	`jnl`	FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization. CoRR Esin Durmus, He He, Mona T. Diab
2020	J	`jnl`	GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. J. Mach. Learn. Res. 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
2020	J	`jnl`	Text Generation by Learning from Off-Policy Demonstrations. CoRR Richard Yuanzhe Pang, He He
2019	B	`conf`	A Dynamic Strategy Coach for Effective Negotiation. SIGdial Yiheng Zhou, He He, Alan W. Black, Yulia Tsvetkov
2019	J	`jnl`	A Dynamic Strategy Coach for Effective Negotiation. CoRR Yiheng Zhou, He He, Alan W. Black, Yulia Tsvetkov
2019	—	`conf`	Dive into Deep Learning for Natural Language Processing. EMNLP/IJCNLP (2) Haibin Lin, Xingjian Shi, Leonard Lausen, Aston Zhang, He He, Sheng Zha, Alexander J. Smola
2019	J	`jnl`	GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. CoRR 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
2019	—	`conf`	Pun Generation with Surprise. NAACL-HLT (1) He He, Nanyun Peng, Percy Liang
2019	J	`jnl`	Pun Generation with Surprise. CoRR He He, Nanyun Peng, Percy Liang
2019	J	`jnl`	Quizbowl: The Case for Incremental Question Answering. CoRR Pedro Rodriguez, Shi Feng, Mohit Iyyer, He He, Jordan L. Boyd-Graber
2019	—	`conf`	Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual. DeepLo@EMNLP-IJCNLP He He, Sheng Zha, Haohan Wang
2019	J	`jnl`	Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual. CoRR He He, Sheng Zha, Haohan Wang
2018	A*	`conf`	Decoupling Strategy and Generation in Negotiation Dialogues. EMNLP He He, Derek Chen, Anusha Balakrishnan, Percy Liang
2018	J	`jnl`	Decoupling Strategy and Generation in Negotiation Dialogues. CoRR He He, Derek Chen, Anusha Balakrishnan, Percy Liang
2018	J	`jnl`	Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer. CoRR Juncen Li, Robin Jia, He He, Percy Liang
2018	—	`conf`	Delete, Retrieve, Generate: a Simple Approach to Sentiment and Style Transfer. NAACL-HLT Juncen Li, Robin Jia, He He, Percy Liang
2018	—	`ed.`	Proceedings of The Third Workshop on Representation Learning for NLP, Rep4NLP@ACL 2018, Melbourne, Australia, July 20, 2018 Rep4NLP@ACL Isabelle Augenstein, Kris Cao, He He, Felix Hill, Spandana Gella, Jamie Kiros, Hongyuan Mei, Dipendra Misra
2018	J	`jnl`	QuAC : Question Answering in Context. CoRR Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang, Luke Zettlemoyer
2018	A*	`conf`	QuAC: Question Answering in Context. EMNLP Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang, Luke Zettlemoyer
2018	—	`conf`	Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context. ACL (1) Urvashi Khandelwal, He He, Peng Qi, Dan Jurafsky
2018	J	`jnl`	Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context. CoRR Urvashi Khandelwal, He He, Peng Qi, Dan Jurafsky
2017	—	`conf`	Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings. ACL (1) He He, Anusha Balakrishnan, Mihail Eric, Percy Liang
2017	J	`jnl`	Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings. CoRR He He, Anusha Balakrishnan, Mihail Eric, Percy Liang
2016	—	`conf`	A Credit Assignment Compiler for Joint Prediction. NIPS Kai-Wei Chang, He He, Stéphane Ross, Hal Daumé III, John Langford
2016	J	`jnl`	Active Information Acquisition. CoRR He He, Paul Mineiro, Nikos Karampatziakis
2016	—	`conf`	Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation. HLT-NAACL He He, Jordan L. Boyd-Graber, Hal Daumé III
2016	A	`conf`	Object detection in 20 questions. WACV Xi Stephen Chen, He He, Larry S. Davis
2016	A*	`conf`	Opponent Modeling in Deep Reinforcement Learning. ICML He He, Jordan L. Boyd-Graber
2016	J	`jnl`	Opponent Modeling in Deep Reinforcement Learning. CoRR He He, Jordan L. Boyd-Graber, Kevin Kwok, Hal Daumé III
2016	—	`—`	Sequential Decisions and Predictions in Natural Language Processing. He He
2015	C	`conf`	Crowdsourcing with multi-dimensional trust. FUSION Xiangyang Liu, He He, John S. Baras
2015	—	`conf`	Hands-on Learning to Search for Structured Prediction. HLT-NAACL Hal Daumé III, John Langford, Kai-Wei Chang, He He, Sudha Rao
2015	J	`jnl`	Learning to Search for Dependencies. CoRR Kai-Wei Chang, He He, Hal Daumé III, John Langford
2015	A*	`conf`	Syntax-based Rewriting for Simultaneous Machine Translation. EMNLP He He, Alvin Grissom II, John Morgan, Jordan L. Boyd-Graber, Hal Daumé III
2015	—	`conf`	Trust-aware optimal crowdsourcing with budget constraint. ICC Xiangyang Liu, He He, John S. Baras
2014	A*	`conf`	Don't Until the Final Verb Wait: Reinforcement Learning for Simultaneous Machine Translation. EMNLP Alvin Grissom II, He He, Jordan L. Boyd-Graber, John Morgan, Hal Daumé III
2014	—	`conf`	Learning to Search in Branch and Bound Algorithms. NIPS He He, Hal Daumé III, Jason Eisner
2014	—	`conf`	Temporal supervised learning for inferring a dialog policy from example conversations. SLT Lihong Li, He He, Jason D. Williams
2013	A*	`conf`	Dynamic Feature Selection for Dependency Parsing. EMNLP He He, Hal Daumé III, Jason Eisner
2012	—	`conf`	Besting the Quiz Master: Crowdsourcing Incremental Classification Games. EMNLP-CoNLL Jordan L. Boyd-Graber, Brianna Satinoff, He He, Hal Daumé III
2012	—	`conf`	Imitation Learning by Coaching. NIPS He He, Hal Daumé III, Jason Eisner
2011	A*	`conf`	Single image super-resolution using Gaussian process regression. CVPR He He, Wan-Chi Siu
2010	B	`conf`	Rare Class Classification by Support Vector Machine. ICPR He He, Ali Ghodsi