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Recent LLMs like DeepSeek-R1 have demonstrated state-of-the-art performance by integrating deep thinking and complex reasoning during generation.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, and 1 others. 2020 · 1901
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Extraction of vn-collocations from text corpora: A feasibility study for german
Elisabeth Breidt. 1996 · 1996
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The structure of discussions that promote reasoning
Clark A. Chinn and Richard C. Anderson. 1998 · 1998
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Comparing corpora using frequency profiling
Paul Rayson and Roger Garside. 2000 · 2000
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Textrank: Bringing order into text
Rada Mihalcea and Paul Tarau. 2004 · 2004
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Quantitative analysis of culture using millions of digitized books
Jean-Baptiste Michel, Yuan Kui Shen, Aviva Presser Aiden, Adrian Veres, Matthew K Gray, Google Books Team, Joseph P Pickett, Dale Hoiberg, Dan Clancy, Peter Norvig, and 1 others. 2011 · 2011
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Deep inside convolutional networks: Visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman. 2014 · 2014
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Understanding intermediate layers using linear classifier probes
Guillaume Alain and Yoshua Bengio. 2016 · 2016
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Reasoning words as linguistic features of exploratory talk: Classroom use and what it can tell us
Maureen Boyd and Yiren Kong. 2017 · 2017
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Interpreting gpt: the logit lens
Nostalgebraist. 2020 · 2020
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An empirical study of textrank for keyword extraction
Mingxi Zhang, Xuemin Li, Shuibo Yue, and Liuqian Yang. 2020 · 2020
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde De Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, and 1 others. 2021 · 2021
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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
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Nelson Elhage, Tristan Hume, Catherine Olsson, Nicholas Schiefer, Tom Henighan, Shauna Kravec, Zac Hatfield-Dodds, Robert Lasenby, Dawn Drain, Carol Chen, and 1 others. 2022 · 2022
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Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
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Locating and editing factual associations in gpt
Kevin Meng, David Bau, Alex Andonian, and Yonatan Belinkov. 2022 · 2022
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Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2022 · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, and 1 others. 2022 · 2022
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Towards monosemanticity: Decomposing language models with dictionary learning, 2023
Trenton Bricken, Adly Templeton, Joshua Batson, Brian Chen, Adam Jermyn, Tom Conerly, Nick Turner, Cem Anil, Carson Denison, Amanda Askell, and 1 others. 2023 · 2023
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Beyond surface: Probing llama across scales and layers
Nuo Chen, Ning Wu, Shining Liang, Ming Gong, Linjun Shou, Dongmei Zhang, and Jia Li. 2023 · 2023
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Sparse autoencoders find highly interpretable features in language models
Hoagy Cunningham, Aidan Ewart, Logan Riggs, Robert Huben, and Lee Sharkey. 2023 · 2023
Cited alongside, same era.
Self-refine: Iterative refinement with self-feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, and 1 others. 2023 · 2023
Mingyu Jin, Qinkai Yu, Jingyuan Huang, Qingcheng Zeng, Zhenting Wang, Wenyue Hua, Haiyan Zhao, Kai Mei, Yanda Meng, Kaize Ding, and 1 others. 2024 · 2024
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Gemma scope: Open sparse autoencoders everywhere all at once on gemma 2
Tom Lieberum, Senthooran Rajamanoharan, Arthur Conmy, Lewis Smith, Nicolas Sonnerat, Vikrant Varma, János Kramár, Anca Dragan, Rohin Shah, and Neel Nanda. 2024 · 2024
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Sparse crosscoders for cross-layer features and model diffing
Jack Lindsey, Adly Templeton, Jonathan Marcus, Thomas Conerly, Joshua Batson, and Christopher Olah. 2024 · 2024
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Sparse feature circuits: Discovering and editing interpretable causal graphs in language models
Samuel Marks, Can Rager, Eric J Michaud, Yonatan Belinkov, David Bau, and Aaron Mueller. 2024 · 2024
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Emergent linear representations in world models of self-supervised sequence models
Neel Nanda, Andrew Lee, and Martin Wattenberg. 2023 · 2023
Cited alongside, same era.
The linear representation hypothesis and the geometry of large language models
Kiho Park, Yo Joong Choe, and Victor Veitch. 2023 · 2023
Cited alongside, same era.
Gpqa: A graduate-level google-proof q&a benchmark
David Rein, Betty Li Hou, Asa Cooper Stickland, Jackson Petty, Richard Yuanzhe Pang, Julien Dirani, Julian Michael, and Samuel R. Bowman. 2023 · 2023
Cited alongside, same era.
Reflexion: Language agents with verbal reinforcement learning
Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. 2023 · 2023
Cited alongside, same era.
SlimPajama: A 627B token cleaned and deduplicated version of RedPajama
Daria Soboleva, Faisal Al-Khateeb, Robert Myers, Jacob R Steeves, Joel Hestness, and Nolan Dey. 2023 · 2023
Cited alongside, same era.
Lmsys-chat-1m: A large-scale real-world llm conversation dataset
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric. P Xing, Joseph E. Gonzalez, Ion Stoica, and Hao Zhang. 2023 · 2023
Cited alongside, same era.
Mechanistic permutability: Match features across layers
Nikita Balagansky, Ian Maksimov, and Daniil Gavrilov. 2024 · 2024
Cited alongside, same era.
Gonçalo Paulo, Alex Mallen, Caden Juang, and Nora Belrose. 2024 · 2024
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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
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Qwq: Reflect deeply on the boundaries of the unknown
Qwen Team. 2024 · 2024
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Scaling monosemanticity: Extracting interpretable features from claude 3 sonnet
Adly Templeton. 2024 · 2024
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Hanqi Yan, Yanzheng Xiang, Guangyi Chen, Yifei Wang, Lin Gui, and Yulan He. 2024 · 2024
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Llama-nemotron: Efficient reasoning models
Akhiad Bercovich, Itay Levy, Izik Golan, Mohammad Dabbah, Ran El-Yaniv, Omri Puny, Ido Galil, Zach Moshe, Tomer Ronen, Najeeb Nabwani, and 1 others. 2025 · 2025
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Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders
Bartosz Cywiński and Kamil Deja. 2025 · 2025
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Towards exploratory talk in secondary-school clil: An empirical study of the cognitive discourse function ‘explore’
Pilar Gerns and Louisa Mortimore. 2025 · 2025
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, and 1 others. 2025 · 2025
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Feature-level insights into artificial text detection with sparse autoencoders
Kristian Kuznetsov, Laida Kushnareva, Polina Druzhinina, Anton Razzhigaev, Anastasia Voznyuk, Irina Piontkovskaya, Evgeny Burnaev, and Serguei Barannikov. 2025 · 2025
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Sparse autoencoders do not find canonical units of analysis
Patrick Leask, Bart Bussmann, Michael T. Pearce, Joseph I. Bloom, Curt Tigges, Noura Al Moubayed, Lee Sharkey, and Neel Nanda. 2025 · 2025
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Niklas Muennighoff, Zitong Yang, Weijia Shi, Xiang Lisa Li, Li Fei-Fei, Hannaneh Hajishirzi, Luke Zettlemoyer, Percy Liang, Emmanuel Candès, and Tatsunori Hashimoto. 2025 · 2025
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Open Thoughts
OpenThoughts. 2025 · 2025
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Route sparse autoencoder to interpret large language models
Wei Shi, Sihang Li, Tao Liang, Mingyang Wan, Guojun Ma, Xiang Wang, and Xiangnan He. 2025 · 2025
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A survey on sparse autoencoders: Interpreting the internal mechanisms of large language models
Dong Shu, Xuansheng Wu, Haiyan Zhao, Daking Rai, Ziyu Yao, Ninghao Liu, and Mengnan Du. 2025 · 2025
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Steering large language models with feature guided activation additions
Samuel Soo, Wesley Teng, and Chandrasekaran Balaganesh. 2025 · 2025
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