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Frontier reasoning models have exhibited incredible capabilities across a wide array of disciplines, driven by posttraining large language models (LLMs) with reinforcement learning (RL).
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Evaluating large language models trained on code
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Competition-level code generation with AlphaCode
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Training language models to follow instructions with human feedback
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Afonso S. Bandeira, Antoine Maillard, Richard Nickl, and Sven Wang · 2022
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GPQA: A graduate-level google-proof q&a benchmark
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Deepseek-math: Advancing mathematical reasoning through step-by-step exploration
Zhihong Shao, Peiyi Wang, Qihao Zhu, Runxin Xu, Junxiao Song, Xiao Bi, Haowei Zhang, Mingchuan Zhang, Y. K. Li, Y. Wu, and Daya Guo · 2024
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Tülu 3: Pushing frontiers in open language model post-training
Nathan Lambert, Jacob Morrison, Valentina Pyatkin, Shengyi Huang, Hamish Ivison, Faeze Brahman, Lester James V Miranda, Alisa Liu, Nouha Dziri, Shane Lyu, et al · 2024
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Probabilistic inference in language models via twisted sequential monte carlo
Stephen Zhao, Rob Brekelmans, Alireza Makhzani, and Roger Grosse · 2024
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Maximizing confidence alone improves reasoning
Mihir Prabhudesai, Lili Chen, Alex Ippoliti, Katerina Fragkiadaki, Hao Liu, and Deepak Pathak · 2025
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Simplerlzoo: Investigating and taming zero reinforcement learning for open base models in the wild
Weihao Zeng, Yuzhen Huang, Qian Liu, Wei Liu, Keqing He, Zejun Ma, and Junxian He · 2025
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Learning to reason without external rewards
Xuandong Zhao, Zhewei Kang, Aosong Feng, Sergey Levine, and Dawn Song · 2025
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Mcmc for multi-modal distributions
Krzysztof Łatuszyński, Matthew T. Moores, and Timothée Stumpf-Fétizon · 2025
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Test-time alignment of diffusion models without reward over-optimization
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Gonçalo R. A. Faria, Sweta Agrawal, António Farinhas, Ricardo Rei, José G. C. de Souza, and André F. T. Martins · 2024
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Marah Abdin, Jyoti Aneja, Harkirat Behl, Sébastien Bubeck, Ronen Eldan, Suriya Gunasekar, Michael Harrison, Russell J. Hewett, Mojan Javaheripi, Piero Kauffmann, James R. Lee, Yin Tat Lee, Yuanzhi Li, Weishung Liu, Caio C. T. Mendes, Anh Nguyen, Eric Price, Gustavo de Rosa, Olli Saarikivi, Adil Salim, Shital Shah, Xin Wang, Rachel Ward, Yue Wu, Dingli Yu, Cyril Zhang, and Yi Zhang · 2024
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Let’s verify step by step
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Length-controlled alpacaeval: A simple way to debias automatic evaluators
Yann Dubois, Balázs Galambosi, Percy Liang, and Tatsunori B. Hashimoto · 2024
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Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, et al · 2025
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Open-reasoner-zero: An open source approach to scaling up reinforcement learning on the base model
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Rewarding the unlikely: Lifting GRPO beyond distribution sharpening
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Rulin Shao, Shuyue Stella Li, Rui Xin, Scott Geng, Yiping Wang, Sewoong Oh, Simon Shaolei Du, Nathan Lambert, Sewon Min, Ranjay Krishna, Yulia Tsvetkov, Hannaneh Hajishirzi, Pang Wei Koh, and Luke Zettlemoyer · 2025
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Proteina: Scaling flow-based protein structure generative models
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Blink of an eye: A simple theory for feature localization in generative models
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