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2020 – today
- 2026
[i16]Fabian Gloeckle, Mantas Baksys, Darius Feher, Kunhao Zheng, Amaury Hayat, Sean B. Holden, Gabriel Synnaeve, Peter W. O'Hearn:
WybeCoder: Verified Imperative Code Generation. CoRR abs/2603.29088 (2026)- [i15]Kunhao Zheng, Pierre Chambon, Juliette Decugis, Jonas Gehring, Taco Cohen, Benjamin Négrevergne, Gabriel Synnaeve:
Extrapolative Weight Averaging Reveals Correctness-Efficiency Frontiers in Code RL. CoRR abs/2605.28751 (2026) - [i14]Pierre Chambon, Kunhao Zheng, Juliette Decugis, Benoît Sagot, Gabriel Synnaeve:
Reinforcement Learning for Code Optimization. CoRR abs/2607.25970 (2026) - 2025
- [c11]Ori Yoran, Kunhao Zheng, Fabian Gloeckle, Jonas Gehring, Gabriel Synnaeve, Taco Cohen:
The KoLMogorov Test: Compression by Code Generation. ICLR 2025 - [c10]Kunhao Zheng, Juliette Decugis, Jonas Gehring, Taco Cohen, Benjamin NéXuanjinggrevergne, Gabriel Synnaeve:
What Makes Large Language Models Reason in (Multi-Turn) Code Generation? ICLR 2025 - [c9]Yunzhen Feng, Ariel Kwiatkowski, Kunhao Zheng, Julia Kempe, Yaqi Duan:
PILAF: Optimal Human Preference Sampling for Reward Modeling. ICML 2025 - [c8]Jonas Gehring, Kunhao Zheng, Jade Copet, Vegard Mella, Taco Cohen, Gabriel Synnaeve:
RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning. ICML 2025 - [c7]Yunhao Tang, Kunhao Zheng, Gabriel Synnaeve, Rémi Munos:
Optimizing Language Models for Inference Time Objectives using Reinforcement Learning. ICML 2025 - [c6]Alexandre Verine, Florian Le Bronnec, Kunhao Zheng, Alexandre Allauzen, Yann Chevaleyre, Benjamin Négrevergne:
Improving Diversity in Language Models: When Temperature Fails, Change the Loss. ICML 2025 - [i13]Yunzhen Feng, Ariel Kwiatkowski, Kunhao Zheng, Julia Kempe, Yaqi Duan:
PILAF: Optimal Human Preference Sampling for Reward Modeling. CoRR abs/2502.04270 (2025) - [i12]Taco Cohen, David W. Zhang, Kunhao Zheng, Yunhao Tang, Rémi Munos, Gabriel Synnaeve:
Soft Policy Optimization: Online Off-Policy RL for Sequence Models. CoRR abs/2503.05453 (2025) - [i11]Ori Yoran, Kunhao Zheng, Fabian Gloeckle, Jonas Gehring, Gabriel Synnaeve, Taco Cohen:
The KoLMogorov Test: Compression by Code Generation. CoRR abs/2503.13992 (2025) - [i10]Yunhao Tang, Kunhao Zheng, Gabriel Synnaeve, Rémi Munos:
Optimizing Language Models for Inference Time Objectives using Reinforcement Learning. CoRR abs/2503.19595 (2025) - [i9]Alexandre Verine, Florian Le Bronnec, Kunhao Zheng, Alexandre Allauzen, Yann Chevaleyre, Benjamin Négrevergne:
Improving Diversity in Language Models: When Temperature Fails, Change the Loss. CoRR abs/2508.09654 (2025) - [i8]FAIR CodeGen team, Jade Copet, Quentin Carbonneaux, Gal Cohen, Jonas Gehring, Jacob Kahn, Jannik Kossen, Felix Kreuk, Emily McMilin, Michel Meyer, Yuxiang Wei, David Zhang, Kunhao Zheng, Jordi Armengol-Estapé, Pedram Bashiri, Maximilian Beck, Pierre Chambon, Abhishek Charnalia, Chris Cummins, Juliette Decugis, Zacharias V. Fisches, François Fleuret, Fabian Gloeckle, Alex Gu, Michael Hassid, Daniel Haziza, Badr Youbi Idrissi, Christian Keller, Rahul Kindi, Hugh Leather, Gallil Maimon, Aram H. Markosyan, Francisco Massa, Pierre-Emmanuel Mazaré, Vegard Mella, Naila Murray, Keyur Muzumdar, Peter W. O'Hearn, Matteo Pagliardini, Dmitrii Pedchenko, Tal Remez, Volker Seeker, Marco Selvi
, Oren Sultan, Sida Wang, Luca Wehrstedt, Ori Yoran, Lingming Zhang, Taco Cohen, Yossi Adi, Gabriel Synnaeve:
CWM: An Open-Weights LLM for Research on Code Generation with World Models. CoRR abs/2510.02387 (2025) - 2024
- [i7]Jonas Gehring, Kunhao Zheng, Jade Copet, Vegard Mella, Taco Cohen, Gabriel Synnaeve:
RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning. CoRR abs/2410.02089 (2024) - [i6]Kunhao Zheng, Juliette Decugis, Jonas Gehring, Taco Cohen, Benjamin Négrevergne, Gabriel Synnaeve:
What Makes Large Language Models Reason in (Multi-Turn) Code Generation? CoRR abs/2410.08105 (2024) - 2023
- [c5]Chen Ju, Kunhao Zheng, Jinxiang Liu, Peisen Zhao, Ya Zhang, Jianlong Chang, Qi Tian, Yanfeng Wang:
Distilling Vision-Language Pre-Training to Collaborate with Weakly-Supervised Temporal Action Localization. CVPR 2023: 14751-14762 - [c4]Tianbo Li, Min Lin, Zheyuan Hu, Kunhao Zheng, Giovanni Vignale, Kenji Kawaguchi, A. H. Castro Neto, Kostya S. Novoselov, Shuicheng Yan:
D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory. ICLR 2023 - [c3]Stanislas Polu, Jesse Michael Han, Kunhao Zheng, Mantas Baksys, Igor Babuschkin, Ilya Sutskever:
Formal Mathematics Statement Curriculum Learning. ICLR 2023 - [i5]Tianbo Li, Min Lin, Zheyuan Hu, Kunhao Zheng, Giovanni Vignale, Kenji Kawaguchi, A. H. Castro Neto, Kostya S. Novoselov, Shuicheng Yan:
D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory. CoRR abs/2303.00399 (2023) - 2022
- [c2]Chen Ju, Tengda Han, Kunhao Zheng, Ya Zhang, Weidi Xie:
Prompting Visual-Language Models for Efficient Video Understanding. ECCV (35) 2022: 105-124 - [c1]Kunhao Zheng, Jesse Michael Han, Stanislas Polu:
miniF2F: a cross-system benchmark for formal Olympiad-level mathematics. ICLR 2022 - [i4]Stanislas Polu, Jesse Michael Han, Kunhao Zheng, Mantas Baksys, Igor Babuschkin, Ilya Sutskever:
Formal Mathematics Statement Curriculum Learning. CoRR abs/2202.01344 (2022) - [i3]Chen Ju, Kunhao Zheng, Jinxiang Liu, Peisen Zhao, Ya Zhang, Jianlong Chang, Yanfeng Wang, Qi Tian:
Distilling Vision-Language Pre-training to Collaborate with Weakly-Supervised Temporal Action Localization. CoRR abs/2212.09335 (2022) - 2021
- [i2]Kunhao Zheng, Jesse Michael Han, Stanislas Polu:
MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics. CoRR abs/2109.00110 (2021) - [i1]Chen Ju, Tengda Han, Kunhao Zheng, Ya Zhang, Weidi Xie:
Prompting Visual-Language Models for Efficient Video Understanding. CoRR abs/2112.04478 (2021)
Coauthor Index
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