Fetching the paper…
Reading the bibliography…
Reinforcement finetuning (RFT) has become a standard approach for enhancing the reasoning capabilities of large language models (LLMs).
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
Earlier work this paper cites.
Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman. 2021 · 2021
Earlier work this paper cites.
Measuring mathematical problem solving with the math dataset
Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt. 2021 · 2021
Earlier work this paper cites.
Solving quantitative reasoning problems with language models
Aitor Lewkowycz, Anders Andreassen, David Dohan, Ethan Dyer, Henryk Michalewski, Vinay Ramasesh, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, and 1 others. 2022 · 2022
Earlier work this paper cites.
TruthfulQA: Measuring how models mimic human falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans. 2022 · 2022
Earlier work this paper cites.
When not to trust language models: Investigating effectiveness and limitations of parametric and non-parametric memories
Alex Mallen, Akari Asai, Victor Zhong, Rajarshi Das, Hannaneh Hajishirzi, and Daniel Khashabi. 2022 · 2022
Earlier work this paper cites.
Mitigating open-vocabulary caption hallucinations
Assaf Ben-Kish, Moran Yanuka, Morris Alper, Raja Giryes, and Hadar Averbuch-Elor. 2023 · 2023
Earlier work this paper cites.
Evaluating hallucinations in chinese large language models
Qinyuan Cheng, Tianxiang Sun, Wenwei Zhang, Siyin Wang, Xiangyang Liu, Mozhi Zhang, Junliang He, Mianqiu Huang, Zhangyue Yin, Kai Chen, and Xipeng Qiu. 2023 · 2023
Earlier work this paper cites.
Hunter Lightman, Vineet Kosaraju, Yura Burda, Harri Edwards, Bowen Baker, Teddy Lee, Jan Leike, John Schulman, Ilya Sutskever, and Karl Cobbe. 2023 · 2023
Earlier work this paper cites.
Discovering language model behaviors with model-written evaluations
Ethan Perez, Sam Ringer, Kamile Lukosiute, Karina Nguyen, Edwin Chen, Scott Heiner, Craig Pettit, Catherine Olsson, Sandipan Kundu, Saurav Kadavath, and 1 others. 2023 · 2023
Earlier work this paper cites.
Aligning large multimodal models with factually augmented rlhf
Zhiqing Sun, Sheng Shen, Shengcao Cao, Haotian Liu, Chunyuan Li, Yikang Shen, Chuang Gan, Liang-Yan Gui, Yu-Xiong Wang, Yiming Yang, and 1 others. 2023 · 2023
Earlier work this paper cites.
Amber: An llm-free multi-dimensional benchmark for mllms hallucination evaluation
Junyang Wang, Yuhang Wang, Guohai Xu, Jing Zhang, Yukai Gu, Haitao Jia, Jiaqi Wang, Haiyang Xu, Ming Yan, Ji Zhang, and 1 others. 2023 · 2023
Earlier work this paper cites.
Simple synthetic data reduces sycophancy in large language models
Jerry Wei, Da Huang, Yifeng Lu, Denny Zhou, and Quoc V Le. 2023 · 2023
Earlier work this paper cites.
Do large language models know what they don’t know?
Zhangyue Yin, Qiushi Sun, Qipeng Guo, Jiawen Wu, Xipeng Qiu, and Xuanjing Huang. 2023 · 2023
Earlier work this paper cites.
How language model hallucinations can snowball
Muru Zhang, Ofir Press, William Merrill, Alisa Liu, and Noah A Smith. 2023 · 2023
Earlier work this paper cites.
HHEM-2.1-Open
Forrest Bao, Miaoran Li, Rogger Luo, and Ofer Mendelevitch. 2024 · 2024
Cited alongside, same era.
Omni-math: A universal olympiad level mathematic benchmark for large language models
Bofei Gao, Feifan Song, Zhe Yang, Zefan Cai, Yibo Miao, Qingxiu Dong, Lei Li, Chenghao Ma, Liang Chen, Runxin Xu, Zhengyang Tang, Benyou Wang, Daoguang Zan, Shanghaoran Quan, Ge Zhang, Lei Sha, Yichang Zhang, Xuancheng Ren, Tianyu Liu, and Baobao Chang. 2024 · 2024
Cited alongside, same era.
Does fine-tuning llms on new knowledge encourage hallucinations?
Zorik Gekhman, Gal Yona, Roee Aharoni, Matan Eyal, Amir Feder, Roi Reichart, and Jonathan Herzig. 2024 · 2024
Cited alongside, same era.
Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Alex Vaughan, Amy Yang, Angela Fan, Anirudh Goyal, Anthony Hartshorn, Aobo Yang, Archi Mitra, Archie Sravankumar, Artem Korenev, Arthur Hinsvark, and 542 others. 2024 · 2024
Cited alongside, same era.
Open-reasoner-zero: An open source approach to scaling up reinforcement learning on the base model
Jingcheng Hu, Yinmin Zhang, Qi Han, Daxin Jiang, Xiangyu Zhang, and Heung-Yeung Shum. 2025 · 2025
Closest in time.
Deepscaler: Surpassing o1-preview with a 1.5b model by scaling rl
Michael Luo, Sijun Tan, Justin Wong, Xiaoxiang Shi, William Y. Tang, Manan Roongta, Colin Cai, Jeffrey Luo, Li Erran Li, Raluca Ada Popa, and Ion Stoica. 2025 · 2025
Closest in time.
Openai o1 system card
OpenAI. 2024 · 2025
Closest in time.
Openai o3 and o4-mini system card
OpenAI. 2025 · 2025
Closest in time.
QwQ-32B: Embracing the Power of Reinforcement Learning
Qwen Team. 2025 · 2025
Closest in time.
Hybridflow: A flexible and efficient rlhf framework
Guangming Sheng, Chi Zhang, Zilingfeng Ye, Xibin Wu, Wang Zhang, Ru Zhang, Yanghua Peng, Haibin Lin, and Chuan Wu. 2025 · 2025
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Chaoqun He, Renjie Luo, Yuzhuo Bai, Shengding Hu, Zhen Leng Thai, Junhao Shen, Jinyi Hu, Xu Han, Yujie Huang, Yuxiang Zhang, Jie Liu, Lei Qi, Zhiyuan Liu, and Maosong Sun. 2024 · 2024
Cited alongside, same era.
Deepseekmath: Pushing the limits of mathematical reasoning in open language models
Zhihong Shao, Peiyi Wang, Qihao Zhu, Runxin Xu, Junxiao Song, Xiao Bi, Haowei Zhang, Mingchuan Zhang, YK Li, Y Wu, and 1 others. 2024 · 2024
Cited alongside, same era.
Benchmarking hallucination in large language models based on unanswerable math word problem
Yuhong Sun, Zhangyue Yin, Qipeng Guo, Jiawen Wu, Xipeng Qiu, and Hui Zhao. 2024 · 2024
Cited alongside, same era.
A comprehensive survey of hallucination mitigation techniques in large language models
S. M Towhidul Islam Tonmoy, S M Mehedi Zaman, Vinija Jain, Anku Rani, Vipula Rawte, Aman Chadha, and Amitava Das. 2024 · 2024
Cited alongside, same era.
Alignment for honesty
Yuqing Yang, Ethan Chern, Xipeng Qiu, Graham Neubig, and Pengfei Liu. 2024 · 2024
Cited alongside, same era.
Rlhf-v: Towards trustworthy mllms via behavior alignment from fine-grained correctional human feedback
Tianyu Yu, Yuan Yao, Haoye Zhang, Taiwen He, Yifeng Han, Ganqu Cui, Jinyi Hu, Zhiyuan Liu, Hai-Tao Zheng, Maosong Sun, and 1 others. 2024 · 2024
Cited alongside, same era.
Phi-4-reasoning technical report
Marah Abdin, Sahaj Agarwal, Ahmed Awadallah, Vidhisha Balachandran, Harkirat Behl, Lingjiao Chen, Gustavo de Rosa, Suriya Gunasekar, Mojan Javaheripi, Neel Joshi, Piero Kauffmann, Yash Lara, Caio César Teodoro Mendes, Arindam Mitra, Besmira Nushi, Dimitris Papailiopoulos, Olli Saarikivi, Shital Shah, Vaishnavi Shrivastava, and 4 others. 2025 · 2025
Cited alongside, same era.
Hallulens: Llm hallucination benchmark
Yejin Bang, Ziwei Ji, Alan Schelten, Anthony Hartshorn, Tara Fowler, Cheng Zhang, Nicola Cancedda, and Pascale Fung. 2025 · 2025
Cited alongside, same era.
Closest in time.
Efficient reinforcement finetuning via adaptive curriculum learning
Taiwei Shi, Yiyang Wu, Linxin Song, Tianyi Zhou, and Jieyu Zhao. 2025 · 2025
Closest in time.
Toward expert-level medical question answering with large language models
Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Mohamed Amin, Le Hou, Kevin Clark, Stephen R Pfohl, Heather Cole-Lewis, and 1 others. 2025 · 2025
Closest in time.
Still-3-1.5b-preview: Enhancing slow thinking abilities of small models through reinforcement learning
RUCAIBox STILL Team. 2025 · 2025
Closest in time.
Mimo: Unlocking the reasoning potential of language model – from pretraining to posttraining
Xiaomi LLM-Core Team. 2025 · 2025
Closest in time.
A minimalist approach to llm reasoning: from rejection sampling to reinforce
Wei Xiong, Jiarui Yao, Yuhui Xu, Bo Pang, Lei Wang, Doyen Sahoo, Junnan Li, Nan Jiang, Tong Zhang, Caiming Xiong, and Hanze Dong. 2025 · 2025
Closest in time.
Dapo: An open-source llm reinforcement learning system at scale
Qiying Yu, Zheng Zhang, Ruofei Zhu, Yufeng Yuan, Xiaochen Zuo, Yu Yue, Tiantian Fan, Gaohong Liu, Lingjun Liu, Xin Liu, and 1 others. 2025 · 2025
Closest in time.
Nemotron-research-tool-n1: Tool-using language models with reinforced reasoning
Shaokun Zhang, Yi Dong, Jieyu Zhang, Jan Kautz, Bryan Catanzaro, Andrew Tao, Qingyun Wu, Zhiding Yu, and Guilin Liu. 2025 · 2025
Closest in time.
Absolute zero: Reinforced self-play reasoning with zero data
Andrew Zhao, Yiran Wu, Yang Yue, Tong Wu, Quentin Xu, Yang Yue, Matthieu Lin, Shenzhi Wang, Qingyun Wu, Zilong Zheng, and Gao Huang. 2025 · 2025
Closest in time.