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Large Reasoning Models (LRMs) extend large language models with explicit, multi-step reasoning traces to enhance transparency and performance on complex tasks.
Uncertainty estimation in autoregressive structured prediction
Andrey Malinin and Mark Gales. 2020 · 2002
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Statistical language models for information retrieval
ChengXiang Zhai. 2008 · 2008
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Language models (mostly) know what they know
Saurav Kadavath, Tom Conerly, Amanda Askell, Tom Henighan, Dawn Drain, Ethan Perez, Nicholas Schiefer, Zac Hatfield-Dodds, Nova DasSarma, Eli Tran-Johnson, Scott Johnston, Sheer El Showk, Andy Jones, Nelson Elhage, Tristan Hume, Anna Chen, Yuntao Bai, Sam Bowman, Stanislav Fort, Deep Ganguli, Danny Hernandez, Josh Jacobson, Jackson Kernion, Shauna Kravec, Liane Lovitt, Kamal Ndousse, Catherine Olsson, Sam Ringer, Dario Amodei, Tom Brown, Jack Clark, Nicholas Joseph, Ben Mann, Sam McCandlish, Chris Olah, and Jared Kaplan. 2022 · 2022
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Chain-of-thought prompting elicits reasoning in large language models
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The internal state of an LLM knows when it’s lying
Amos Azaria and Tom M. Mitchell. 2023 · 2023
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Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, and Ting Liu. 2023 · 2023
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Semantic uncertainty: Linguistic invariances for uncertainty estimation in natural language generation
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Knowledge editing through chain-of-thought
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An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, Huan Lin, Jian Yang, Jianhong Tu, Jianwei Zhang, Jianxin Yang, Jiaxi Yang, Jingren Zhou, Junyang Lin, Kai Dang, Keming Lu, Keqin Bao, Kexin Yang, Le Yu, Mei Li, Mingfeng Xue, Pei Zhang, Qin Zhu, Rui Men, Runji Lin, Tianhao Li, Tianyi Tang, Tingyu Xia, Xingzhang Ren, Xuancheng Ren, Yang Fan, Yang Su, Yichang Zhang, Yu Wan, Yuqiong Liu, Zeyu Cui, Zhenru Zhang, and Zihan Qiu. 2024 · 2024
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Relevance feedback with brain signals
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Chain-of-thought reasoning in the wild is not always faithful
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Reasoning language models: A blueprint
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Hallucination detection in llms using spectral features of attention maps
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Gemini 2.5: Our most intelligent ai model
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
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Decoupling knowledge and context: An efficient and effective retrieval augmented generation framework via cross attention
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rstar-math: Small llms can master math reasoning with self-evolved deep thinking
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Vectara Hallucination Leaderboard
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A survey of frontiers in llm reasoning: Inference scaling, learning to reason, and agentic systems
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