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Chain-of-Thought (CoT) reasoning enhances Large Language Models (LLMs) by encouraging step-by-step reasoning in natural language.
Multi-task learning with deep neural networks: A survey
Michael Crawshaw. 2020 · 2009
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Thinking, fast and slow
Daniel Kahneman. 2011 · 2011
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Solving general arithmetic word problems
Subhro Roy and Dan Roth. 2015 · 2015
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MAWPS: A math word problem repository
Rik Koncel-Kedziorski, Subhro Roy, Aida Amini, Nate Kushman, and Hannaneh Hajishirzi. 2016 · 2016
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Conceptnet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi. 2017 · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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CommonsenseQA: A question answering challenge targeting commonsense knowledge
Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant. 2019 · 2019
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Enhancing auto-regressive chain-of-thought through loop-aligned reasoning
Qifan Yu, Zhenyu He, Sijie Li, Xun Zhou, Jun Zhang, Jingjing Xu, and Di He. 2025 · 2019
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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
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Knowledge distillation: A survey
Jianping Gou, Baosheng Yu, Stephen J. Maybank, and Dacheng Tao. 2021 · 2021
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The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant. 2021 · 2021
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Prefix-tuning: Optimizing continuous prompts for generation
Xiang Lisa Li and Percy Liang. 2021 · 2021
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Analyzing curriculum learning for sentiment analysis along task difficulty, pacing and visualization axes
Anvesh Rao Vijjini, Kaveri Anuranjana, and Radhika Mamidi. 2021 · 2021
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LoRA: Low-rank adaptation of large language models
Edward J Hu, yelong shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022 · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022
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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 Chi, Quoc V Le, and Denny Zhou. 2022 · 2022
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Implicit chain of thought reasoning via knowledge distillation
Yuntian Deng, Kiran Prasad, Roland Fernandez, Paul Smolensky, Vishrav Chaudhary, and Stuart Shieber. 2023 · 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 · 2023
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Large language models are reasoning teachers
Namgyu Ho, Laura Schmid, and Se-Young Yun. 2023 · 2023
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Distilling step-by-step! outperforming larger language models with less training data and smaller model sizes
Cheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alex Ratner, Ranjay Krishna, Chen-Yu Lee, and Tomas Pfister. 2023 · 2023
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Hello gpt-4o
OpenAI. 2024 · 2024
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Let’s think dot by dot: Hidden computation in transformer language models
Jacob Pfau, William Merrill, and Samuel R. Bowman. 2024 · 2024
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What formal languages can transformers express? a survey
Lena Strobl, William Merrill, Gail Weiss, David Chiang, and Dana Angluin. 2024 · 2024
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A survey on knowledge distillation of large language models
Xiaohan Xu, Ming Li, Chongyang Tao, Tao Shen, Reynold Cheng, Jinyang Li, Can Xu, Dacheng Tao, and Tianyi Zhou. 2024 · 2024
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Self-distillation bridges distribution gap in language model fine-tuning
Zhaorui Yang, Tianyu Pang, Haozhe Feng, Han Wang, Wei Chen, Minfeng Zhu, and Qian Liu. 2024 · 2024
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Sheng Liu, Haotian Ye, Lei Xing, and James Y. Zou. 2023 · 2023
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Self-instruct: Aligning language models with self-generated instructions
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, and Hannaneh Hajishirzi. 2023 · 2023
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Claude 3.5 sonnet
Anthropic. 2024 · 2024
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Compressed chain of thought: Efficient reasoning through dense representations
Jeffrey Cheng and Benjamin Van Durme. 2024 · 2024
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From explicit cot to implicit cot: Learning to internalize cot step by step
Yuntian Deng, Yejin Choi, and Stuart Shieber. 2024 · 2024
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In-context autoencoder for context compression in a large language model
Tao Ge, Hu Jing, Lei Wang, Xun Wang, Si-Qing Chen, and Furu Wei. 2024 · 2024
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Our next-generation model: Gemini 1.5
Google. 2024 · 2024
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Yijiang River Dong, Hongzhou Lin, Mikhail Belkin, Ramon Huerta, and Ivan Vulić. 2025 · 2025
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Scaling up test-time compute with latent reasoning: A recurrent depth approach
Jonas Geiping, Sean Michael McLeish, Neel Jain, John Kirchenbauer, Siddharth Singh, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, and Tom Goldstein. 2025 · 2025
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500xCompressor: Generalized prompt compression for large language models
Zongqian Li, Yixuan Su, and Nigel Collier. 2025 · 2025
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Critical tokens matter: Token-level contrastive estimation enhances LLM’s reasoning capability
Zicheng Lin, Tian Liang, Jiahao Xu, Qiuzhi Liu, Xing Wang, Ruilin Luo, Chufan Shi, Siheng Li, Yujiu Yang, and Zhaopeng Tu. 2025 · 2025
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Deliberation in latent space via differentiable cache augmentation
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LLMs know more than they show: On the intrinsic representation of LLM hallucinations
Hadas Orgad, Michael Toker, Zorik Gekhman, Roi Reichart, Idan Szpektor, Hadas Kotek, and Yonatan Belinkov. 2025 · 2025
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Reasoning with latent thoughts: On the power of looped transformers
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Token assorted: Mixing latent and text tokens for improved language model reasoning
DiJia Su, Hanlin Zhu, Yingchen Xu, Jiantao Jiao, Yuandong Tian, and Qinqing Zheng. 2025 · 2025
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SoftCoT: Soft chain-of-thought for efficient reasoning with LLMs
Yige Xu, Xu Guo, Zhiwei Zeng, and Chunyan Miao. 2025 · 2025
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Are NLP models really able to solve simple math word problems?
Arkil Patel, Satwik Bhattamishra, and Navin Goyal. 2021 · 2094
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