publications

2026

1. Does RL Expand the Capability Boundary of LLM Agents? A PASS@(k,T) Analysis

   Zhiyuan Zhai, Wenjing Yan, Xiaodan Shao, and 1 more author

   arXiv preprint arXiv:2604.14877, 2026

   Bib

   @article{zhai2026passkt,
     title = {Does RL Expand the Capability Boundary of LLM Agents? A PASS@(k,T) Analysis},
     author = {Zhai, Zhiyuan and Yan, Wenjing and Shao, Xiaodan and Wang, Xin},
     journal = {arXiv preprint arXiv:2604.14877},
     year = {2026},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG}
   }

2025

1. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

   DeepSeek-AI

   arXiv preprint arXiv:2501.12948, 2025

   Bib

   @article{deepseekr1_2025,
     title = {DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning},
     author = {{DeepSeek-AI}},
     journal = {arXiv preprint arXiv:2501.12948},
     year = {2025},
     archiveprefix = {arXiv},
     primaryclass = {cs.CL}
   }

2. Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?

   Yang Yue, Zhiqi Chen, Rui Lu, and 4 more authors

   arXiv preprint arXiv:2504.13837, 2025

   Bib

   @article{yue2025rlreasoning,
     title = {Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?},
     author = {Yue, Yang and Chen, Zhiqi and Lu, Rui and Zhao, Andrew and Wang, Zhaokai and Song, Shiji and Huang, Gao},
     journal = {arXiv preprint arXiv:2504.13837},
     year = {2025},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG}
   }

3. A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility

   Andreas Hochlehnert, Hardik Bhatnagar, Vishaal Udandarao, and 3 more authors

   arXiv preprint arXiv:2504.07086, 2025

   Bib

   @article{hochlehnert2025sober,
     title = {A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility},
     author = {Hochlehnert, Andreas and Bhatnagar, Hardik and Udandarao, Vishaal and Albanie, Samuel and Prabhu, Ameya and Bethge, Matthias},
     journal = {arXiv preprint arXiv:2504.07086},
     year = {2025},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG}
   }

4. DAPO: An Open-Source LLM Reinforcement Learning System at Scale

   Qiying Yu, Zheng Zhang, Ruofei Zhu, and 8 more authors

   arXiv preprint arXiv:2503.14476, 2025

   Bib

   @article{yu2025dapo,
     title = {DAPO: An Open-Source LLM Reinforcement Learning System at Scale},
     author = {Yu, Qiying and Zhang, Zheng and Zhu, Ruofei and Yuan, Yufeng and Zuo, Xiaochen and Yue, Yu and Fan, Tiantian and Liu, Gaohong and Liu, Lingjun and Liu, Xin and others},
     journal = {arXiv preprint arXiv:2503.14476},
     year = {2025},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG}
   }

5. Understanding R1-Zero-Like Training: A Critical Perspective

   Zichen Liu, Changyu Chen, Wenjun Li, and 5 more authors

   arXiv preprint arXiv:2503.20783, 2025

   Bib

   @article{liu2025drgrpo,
     title = {Understanding R1-Zero-Like Training: A Critical Perspective},
     author = {Liu, Zichen and Chen, Changyu and Li, Wenjun and Qi, Penghui and Pang, Tianyu and Du, Chao and Lee, Wee Sun and Lin, Min},
     journal = {arXiv preprint arXiv:2503.20783},
     year = {2025},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG}
   }

6. Spurious Rewards: Rethinking Training Signals in RLVR

   Rulin Shao, Shuyue Stella Li, Rui Xin, and 8 more authors

   arXiv preprint arXiv:2506.10947, 2025

   Bib

   @article{shao2025spuriousrewards,
     title = {Spurious Rewards: Rethinking Training Signals in RLVR},
     author = {Shao, Rulin and Li, Shuyue Stella and Xin, Rui and Geng, Scott and Wang, Yiping and Oh, Sewoong and Du, Simon Shaolei and Lambert, Nathan and Min, Sewon and Krishna, Ranjay and others},
     journal = {arXiv preprint arXiv:2506.10947},
     year = {2025},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG}
   }

2024

1. DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

   Zhihong Shao, Peiyi Wang, Qihao Zhu, and 6 more authors

   arXiv preprint arXiv:2402.03300, 2024

   Bib

   @article{shao2024deepseekmath,
     title = {DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models},
     author = {Shao, Zhihong and Wang, Peiyi and Zhu, Qihao and Xu, Runxin and Song, Junxiao and Zhang, Mingchuan and Li, Y. K. and Wu, Y. and Guo, Daya},
     journal = {arXiv preprint arXiv:2402.03300},
     year = {2024},
     archiveprefix = {arXiv},
     primaryclass = {cs.CL}
   }

2. Tulu 3: Pushing Frontiers in Open Language Model Post-Training

   Nathan Lambert, Jacob Morrison, Valentina Pyatkin, and 8 more authors

   arXiv preprint arXiv:2411.15124, 2024

   Bib

   @article{lambert2024tulu3,
     title = {Tulu 3: Pushing Frontiers in Open Language Model Post-Training},
     author = {Lambert, Nathan and Morrison, Jacob and Pyatkin, Valentina and Huang, Shengyi and Ivison, Hamish and Brahman, Faeze and Miranda, Lester James V. and Liu, Alisa and Dziri, Nouha and Lyu, Shane and others},
     journal = {arXiv preprint arXiv:2411.15124},
     year = {2024},
     archiveprefix = {arXiv},
     primaryclass = {cs.CL}
   }

3. Are Your LLMs Capable of Stable Reasoning?

   Junnan Liu, Hongwei Liu, Linchen Xiao, and 6 more authors

   arXiv preprint arXiv:2412.13147, 2024

   Bib

   @article{liu2024stablereasoning,
     title = {Are Your LLMs Capable of Stable Reasoning?},
     author = {Liu, Junnan and Liu, Hongwei and Xiao, Linchen and Wang, Ziyi and Liu, Kuikun and Gao, Songyang and Zhang, Wenwei and Zhang, Songyang and Chen, Kai},
     journal = {arXiv preprint arXiv:2412.13147},
     year = {2024},
     archiveprefix = {arXiv},
     primaryclass = {cs.CL}
   }

2023

1. Direct Preference Optimization: Your Language Model is Secretly a Reward Model

   Rafael Rafailov, Archit Sharma, Eric Mitchell, and 3 more authors

   Advances in Neural Information Processing Systems (NeurIPS), 2023

   Bib

   @article{rafailov2023dpo,
     title = {Direct Preference Optimization: Your Language Model is Secretly a Reward Model},
     author = {Rafailov, Rafael and Sharma, Archit and Mitchell, Eric and Ermon, Stefano and Manning, Christopher D. and Finn, Chelsea},
     journal = {Advances in Neural Information Processing Systems (NeurIPS)},
     year = {2023},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG}
   }

2022

1. Training Language Models to Follow Instructions with Human Feedback

   Long Ouyang, Jeffrey Wu, Xu Jiang, and 8 more authors

   Advances in Neural Information Processing Systems (NeurIPS), 2022

   Bib

   @article{ouyang2022instructgpt,
     title = {Training Language Models to Follow Instructions with Human Feedback},
     author = {Ouyang, Long and Wu, Jeffrey and Jiang, Xu and Almeida, Diogo and Wainwright, Carroll L. and Mishkin, Pamela and Zhang, Chong and Agarwal, Sandhini and Slama, Katarina and Ray, Alex and others},
     journal = {Advances in Neural Information Processing Systems (NeurIPS)},
     year = {2022},
     archiveprefix = {arXiv},
     primaryclass = {cs.CL}
   }

2. Defining and Characterizing Reward Hacking

   Joar Skalse, Nikolaus H. R. Howe, Dmitrii Krasheninnikov, and 1 more author

   Advances in Neural Information Processing Systems (NeurIPS), 2022

   Bib

   @article{skalse2022rewardhacking,
     title = {Defining and Characterizing Reward Hacking},
     author = {Skalse, Joar and Howe, Nikolaus H. R. and Krasheninnikov, Dmitrii and Krueger, David},
     journal = {Advances in Neural Information Processing Systems (NeurIPS)},
     year = {2022},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG}
   }

2021

1. Evaluating Large Language Models Trained on Code

   Mark Chen, Jerry Tworek, Heewoo Jun, and 8 more authors

   arXiv preprint arXiv:2107.03374, 2021

   Bib

   @article{chen2021codex,
     title = {Evaluating Large Language Models Trained on Code},
     author = {Chen, Mark and Tworek, Jerry and Jun, Heewoo and Yuan, Qiming and de Oliveira Pinto, Henrique Ponde and Kaplan, Jared and Edwards, Harri and Burda, Yuri and Joseph, Nicholas and Brockman, Greg and others},
     journal = {arXiv preprint arXiv:2107.03374},
     year = {2021},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG}
   }

2. Measuring Mathematical Problem Solving With the MATH Dataset

   Dan Hendrycks, Collin Burns, Saurav Kadavath, and 5 more authors

   NeurIPS Datasets and Benchmarks Track, 2021

   Bib

   @article{hendrycks2021math,
     title = {Measuring Mathematical Problem Solving With the MATH Dataset},
     author = {Hendrycks, Dan and Burns, Collin and Kadavath, Saurav and Arora, Akul and Basart, Steven and Tang, Eric and Song, Dawn and Steinhardt, Jacob},
     journal = {NeurIPS Datasets and Benchmarks Track},
     year = {2021},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG}
   }

3. Training Verifiers to Solve Math Word Problems

   Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, and 9 more authors

   arXiv preprint arXiv:2110.14168, 2021

   Bib

   @article{cobbe2021gsm8k,
     title = {Training Verifiers to Solve Math Word Problems},
     author = {Cobbe, Karl and Kosaraju, Vineet and Bavarian, Mohammad and Chen, Mark and Jun, Heewoo and Kaiser, Lukasz and Plappert, Matthias and Tworek, Jerry and Hilton, Jacob and Nakano, Reiichiro and Hesse, Christopher and Schulman, John},
     journal = {arXiv preprint arXiv:2110.14168},
     year = {2021},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG}
   }

2017

1. Proximal Policy Optimization Algorithms

   John Schulman, Filip Wolski, Prafulla Dhariwal, and 2 more authors

   arXiv preprint arXiv:1707.06347, 2017

   Bib

   @article{schulman2017ppo,
     title = {Proximal Policy Optimization Algorithms},
     author = {Schulman, John and Wolski, Filip and Dhariwal, Prafulla and Radford, Alec and Klimov, Oleg},
     journal = {arXiv preprint arXiv:1707.06347},
     year = {2017},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG}
   }

1967

1. Vision

   

   Letters on wave mechanics

   Albert Einstein, Erwin Schrödinger, Max Planck, and 2 more authors

   1967

   Bib

   @book{przibram1967letters,
     title = {Letters on wave mechanics},
     author = {Einstein, Albert and Schrödinger, Erwin and Planck, Max and Lorentz, Hendrik Antoon and Przibram, Karl},
     year = {1967},
     publisher = {Vision},
   }

1956

1. 

   Investigations on the Theory of the Brownian Movement

   Albert Einstein

   1956

   Bib

   @book{einstein1956investigations,
     title = {Investigations on the Theory of the Brownian Movement},
     author = {Einstein, Albert},
     year = {1956},
     publisher = {Courier Corporation},
   }

1950

1. AJP

   The meaning of relativity

   Albert Einstein and AH Taub

   American Journal of Physics, 1950

   Bib

   @article{einstein1950meaning,
     title = {The meaning of relativity},
     author = {Einstein, Albert and Taub, AH},
     journal = {American Journal of Physics},
     volume = {18},
     number = {6},
     pages = {403--404},
     year = {1950},
     publisher = {American Association of Physics Teachers}
   }

1935

1. PhysRev

   Can Quantum-Mechanical Description of Physical Reality Be Considered Complete?

   A. Einstein^*†, B. Podolsky^*, and N. Rosen^*

   Phys. Rev., New Jersey. More Information can be found here , May 1935

   Abs DOI HTML PDF Video

   

   In a complete theory there is an element corresponding to each element of reality. A sufficient condition for the reality of a physical quantity is the possibility of predicting it with certainty, without disturbing the system. In quantum mechanics in the case of two physical quantities described by non-commuting operators, the knowledge of one precludes the knowledge of the other. Then either (1) the description of reality given by the wave function in quantum mechanics is not complete or (2) these two quantities cannot have simultaneous reality. Consideration of the problem of making predictions concerning a system on the basis of measurements made on another system that had previously interacted with it leads to the result that if (1) is false then (2) is also false. One is thus led to conclude that the description of reality as given by a wave function is not complete.

1920

1. Relativity: the Special and General Theory

   Albert Einstein

   1920

   HTML

1905

1. Über die von der molekularkinetischen Theorie der Wärme geforderte Bewegung von in ruhenden Flüssigkeiten suspendierten Teilchen

   A. Einstein

   Annalen der physik, 1905
2. Ann. Phys.

   Un the movement of small particles suspended in statiunary liquids required by the molecular-kinetic theory 0f heat

   A. Einstein

   Ann. Phys., 1905
3. On the electrodynamics of moving bodies

   A. Einstein

   1905
4. Ann. Phys.

   Über einen die Erzeugung und Verwandlung des Lichtes betreffenden heuristischen Gesichtspunkt

   Albert Einstein

   Ann. Phys., 1905

   Nobel Prize Abs DOI Bib

   Albert Einstein receveid the Nobel Prize in Physics 1921 for his services to Theoretical Physics, and especially for his discovery of the law of the photoelectric effect

   This is the abstract text.

   @article{einstein1905photoelectriceffect,
     title = {{{\"U}ber einen die Erzeugung und Verwandlung des Lichtes betreffenden heuristischen Gesichtspunkt}},
     author = {Einstein, Albert},
     journal = {Ann. Phys.},
     volume = {322},
     number = {6},
     pages = {132--148},
     year = {1905},
     doi = {10.1002/andp.19053220607},
   }