Are Reasoning Models More Prone to Hallucination?

Obtaining well calibrated probabilities using bayesian binning

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Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension

Mandar Joshi, Eunsol Choi, Daniel S Weld, and Luke Zettlemoyer · 2017

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Mastering the game of go without human knowledge

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Large language models are zero-shot reasoners

Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022

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Training language models to follow instructions with human feedback

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Chain-of-thought prompting elicits reasoning in large language models

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, and Denny Zhou · 2022

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STaR: Bootstrapping reasoning with reasoning

Eric Zelikman, Yuhuai Wu, Jesse Mu, and Noah Goodman · 2022

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Benchmarking foundation models with language-model-as-an-examiner

Yushi Bai, Jiahao Ying, Yixin Cao, Xin Lv, Yuze He, Xiaozhi Wang, Jifan Yu, Kaisheng Zeng, Yijia Xiao, Haozhe Lyu, Jiayin Zhang, Juanzi Li, and Lei Hou · 2023

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Probabilistic tree-of-thought reasoning for answering knowledge-intensive complex questions

Shulin Cao, Jiajie Zhang, Jiaxin Shi, Xin Lv, Zijun Yao, Qi Tian, Lei Hou, and Juanzi Li · 2023

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Program of thoughts prompting: Disentangling computation from reasoning for numerical reasoning tasks

Wenhu Chen, Xueguang Ma, Xinyi Wang, and William W. Cohen · 2023

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Specializing smaller language models towards multi-step reasoning

Yao Fu, Hao Peng, Litu Ou, Ashish Sabharwal, and Tushar Khot · 2023

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Strategic reasoning with language models

Original

Kanishk Gandhi, Dorsa Sadigh, and Noah Goodman · 2023

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PAL: program-aided language models

Luyu Gao, Aman Madaan, Shuyan Zhou, Uri Alon, Pengfei Liu, Yiming Yang, Jamie Callan, and Graham Neubig · 2023

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An empirical study of catastrophic forgetting in large language models during continual fine-tuning

Original

Yun Luo, Zhen Yang, Fandong Meng, Yafu Li, Jie Zhou, and Yue Zhang · 2023

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Teaching small language models to reason

Lucie Charlotte Magister, Jonathan Mallinson, Jakub Adamek, Eric Malmi, and Aliaksei Severyn · 2023

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Automatic chain of thought prompting in large language models

Zhuosheng Zhang, Aston Zhang, Mu Li, and Alex Smola · 2023

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Judging llm-as-a-judge with mt-bench and chatbot arena

Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica · 2023

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On the calibration of large language models and alignment

Chiwei Zhu, Benfeng Xu, Quan Wang, Yongdong Zhang, and Zhendong Mao · 2023

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Evaluating generative language models in information extraction as subjective question correction

Yuchen Fan, Yantao Liu, Zijun Yao, Jifan Yu, Lei Hou, and Juanzi Li · 2024

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A survey of confidence estimation and calibration in large language models

Measuring short-form factuality in large language models

Original

Jason Wei, Nguyen Karina, Hyung Won Chung, Yunxin Joy Jiao, Spencer Papay, Amelia Glaese, John Schulman, and William Fedus · 2024

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Glm-4-0414 model series

Team GLM · 2025

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Deepseek-R1: Incentivizing reasoning capability in llms via reinforcement learning

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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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Deepmath-103k: A large-scale, challenging, decontaminated, and verifiable mathematical dataset for advancing reasoning

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Zhiwei He, Tian Liang, Jiahao Xu, Qiuzhi Liu, Xingyu Chen, Yue Wang, Linfeng Song, Dian Yu, Zhenwen Liang, Wenxuan Wang, et al · 2025

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Advancing language model reasoning through reinforcement learning and inference scaling