---
title: "He He — all works — Elamur Research"
description: "All 32 works of He He in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
canonical: "https://research.elamur.ai/free/en/authors/he-he/works/"
---
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# He He — all works

32 works · [← He He](https://md.research.elamur.ai/free/en/authors/he-he/)

1. **[QuAC: Question Answering in Context](https://md.research.elamur.ai/free/en/papers/choi-2018-quac-question-answering-context/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eunsol Choi, He He, Mohit Iyyer, et al.*2018 · 1,066 citations*
2. **[Solving olympiad geometry without human demonstrations](https://md.research.elamur.ai/free/en/papers/trinh-2024-solving-olympiad-geometry-without-human/) [Nature](https://md.research.elamur.ai/free/en/venues/nature/)**Trieu H. Trinh, Yuhuai Wu, Quoc V. Le, et al.*2024 · 498 citations*
3. **[Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context](https://md.research.elamur.ai/free/en/papers/khandelwal-2018-sharp-nearby-fuzzy-far-away/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Urvashi Khandelwal, He He, Peng Qi, et al.*2018 · 399 citations*
4. **[FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/durmus-2020-feqa-question-answering-evaluation-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Esin Durmus, He He, Mona Diab*2020 · 359 citations*
5. [**Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer**Juncen Li, Robin Jia, He He, et al.*Machine translation · 351 citations*](https://md.research.elamur.ai/free/en/papers/li-2018-delete-retrieve-generate-simple-approach/)
6. **[Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual](https://md.research.elamur.ai/free/en/papers/he-2019-unlearn-dataset-bias-natural-language/) [Workshop on Deep Learning Approaches for Low-Resource NLP](https://md.research.elamur.ai/free/en/venues/workshop-on-deep-learning-approaches-for-low-resource-nlp/)**He He, Sheng Zha, Haohan Wang*2019 · 260 citations*
7. **[Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings ↗](https://aclanthology.org/P17-1162/) Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**He He et al.*2017 · 258 citations*
8. [**Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought arXiv:2210.01240**Abulhair Saparov, He He*2022 · 244 citations*](https://md.research.elamur.ai/free/en/papers/saparov-2022-language-models-greedy-reasoners-systematic/)
9. **[Decoupling Strategy and Generation in Negotiation Dialogues](https://md.research.elamur.ai/free/en/papers/he-2018-decoupling-strategy-generation-negotiation-dialogues/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**He He, Derek Chen, Anusha Balakrishnan, et al.*2018 · 236 citations*
10. **[QuALITY: Question Answering with Long Input Texts, Yes!](https://md.research.elamur.ai/free/en/papers/pang-2022-quality-question-answering-long-input/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, et al.*2022 · 167 citations*
11. **[Meta-learning via Language Model In-context Tuning ↗](https://arxiv.org/abs/2110.07814) arXiv:2110.07814 · no summary yet**Yanda Chen et al.*2021 · 160 citations*
12. **[Iterative Reasoning Preference Optimization](https://md.research.elamur.ai/free/en/papers/pang-2024-iterative-reasoning-preference-optimization/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.*2024 · 153 citations*
13. **[The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models](https://md.research.elamur.ai/free/en/papers/kirk-2024-prism-alignment-dataset-participatory-representative/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hannah Rose Kirk, Alexander Whitefield, Paul Rottger, et al.*2024 · 133 citations*
14. **[Pun Generation with Surprise ↗](https://aclanthology.org/N19-1172/) Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) · no summary yet**He He, Nanyun Peng, Percy Liang*2019 · 106 citations*
15. **[Types of Out-of-Distribution Texts and How to Detect Them ↗](https://aclanthology.org/2021.emnlp-main.835/) Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · no summary yet**Udit Arora, William Huang, He He*2021 · 103 citations*
16. **[Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation ↗](https://aclanthology.org/N16-1111/) Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yet**He He, Jordan Boyd-Graber, Hal Daumé III*2016 · 86 citations*
17. **[Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples](https://md.research.elamur.ai/free/en/papers/saparov-2023-testing-general-deductive-reasoning-capacity/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, et al.*2023 · 84 citations*
18. [**Does Writing with Language Models Reduce Content Diversity? arXiv:2309.05196**Vishakh Padmakumar, He He*2023 · 82 citations*](https://md.research.elamur.ai/free/en/papers/padmakumar-2023-writing-language-models-reduce-content/)
19. **[Reasoning Models Know When They're Right: Probing Hidden States for Self-Verification ↗](https://arxiv.org/abs/2504.05419) arXiv:2504.05419 · no summary yet**Anqi Zhang et al.*2025 · 52 citations*
20. **[Measuring Inductive Biases of In-Context Learning with Underspecified Demonstrations ↗](https://aclanthology.org/2023.acl-long.632/) Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Chenglei Si et al.*2023 · 42 citations*
21. **[Syntax-based Rewriting for Simultaneous Machine Translation ↗](https://aclanthology.org/D15-1006/) Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing · no summary yet**He He et al.*2015 · 42 citations*
22. **[Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations ↗](https://arxiv.org/abs/2307.08678) arXiv (Cornell University) · no summary yet**Yanda Chen et al.*2023 · 41 citations*
23. **[ARGUS: Visualization of AI-Assisted Task Guidance in AR ↗](https://doi.org/10.1109/tvcg.2023.3327396) IEEE Transactions on Visualization and Computer Graphics · no summary yet**Sonia Castelo et al.*2023 · 38 citations*
24. **[Language Models Learn to Mislead Humans via RLHF ↗](https://arxiv.org/abs/2409.12822) arXiv (Cornell University) · no summary yet**Jiaxin Wen et al.*2024 · 33 citations*
25. **[Leveraging Implicit Feedback from Deployment Data in Dialogue ↗](https://aclanthology.org/2024.eacl-short.8/) Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers) · no summary yet**Richard Yuanzhe Pang et al.*2024 · 12 citations*
26. **[Amortized Noisy Channel Neural Machine Translation ↗](https://aclanthology.org/2022.inlg-main.11/) Proceedings of the 15th International Conference on Natural Language Generation · no summary yet**Richard Yuanzhe Pang, He He, Kyunghyun Cho*2022 · 9 citations*
27. **[Unsupervised Elicitation of Language Models ↗](https://arxiv.org/abs/2506.10139) arXiv (Cornell University) · no summary yet**Jiaxin Wen et al.*2025 · 2 citations*
28. **[Show Your Work with Confidence: Confidence Bands for Tuning Curves ↗](https://aclanthology.org/2024.naacl-long.189/) Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) · no summary yet**Nicholas Lourie, Kyunghyun Cho, He He*2024 · 2 citations*
29. **[Hyperparameter Loss Surfaces Are Simple Near their Optima ↗](https://arxiv.org/abs/2510.02721) arXiv (Cornell University) · no summary yet**Nicholas Lourie, He He, Kyunghyun Cho*2025 · 1 citation*
30. **[Spontaneous Reward Hacking in Iterative Self-Refinement ↗](https://arxiv.org/abs/2407.04549) arXiv (Cornell University) · no summary yet**Jane Pan et al.*2024 · 1 citation*
31. **[PaintBench: Deterministic Evaluation of Precise Visual Editing ↗](https://arxiv.org/abs/2606.00188) arXiv (Cornell University) · no summary yet**Xu, Kai et al.*2026*
32. **[Training Continuous Chain of Thought Models: A Tale of Two Regimes ↗](https://arxiv.org/abs/2607.16972) arXiv (Cornell University) · no summary yet**Yerram Varun, He He, Eunsol Choi*2026*