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Sparse Autoencoders (SAEs) have recently gained attention as a means to improve the interpretability and steerability of Large Language Models (LLMs), both of which are essential for AI safety.
Sparse coding with an overcomplete basis set: A strategy employed by v1?
Bruno A Olshausen and David J Field · 1997
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Alireza Makhzani and Brendan Frey · 2013
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Adam: A method for stochastic optimization, 2017
Diederik P. Kingma and Jimmy Ba · 2017
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Feature visualization
Chris Olah, Alexander Mordvintsev, and Ludwig Schubert · 2017
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Linear algebraic structure of word senses, with applications to polysemy
Sanjeev Arora, Yuanzhi Li, Yingyu Liang, Tengyu Ma, and Andrej Risteski · 2018
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Benchmarking representation learning for natural world image collections
Grant Van Horn, Elijah Cole, Sara Beery, Kimberly Wilber, Serge Belongie, and Oisin Mac Aodha · 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, et al · 2022
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Matryoshka representation learning
Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham Kakade, Prateek Jain, et al · 2022
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Slip: Self-supervision meets language-image pre-training
Norman Mu, Alexander Kirillov, David Wagner, and Saining Xie · 2022
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Towards monosemanticity: Decomposing language models with dictionary learning
Trenton Bricken, Adly Templeton, Joshua Batson, Brian Chen, Adam Jermyn, Tom Conerly, Nick Turner, Cem Anil, Carson Denison, Amanda Askell, et al · 2023
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality, March 2023
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing · 2023
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InstructBLIP: Towards general-purpose vision-language models with instruction tuning
Wenliang Dai, Junnan Li, Dongxu Li, Anthony Tiong, Junqi Zhao, Weisheng Wang, Boyang Li, Pascale Fung, and Steven Hoi · 2023
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Rosetta neurons: Mining the common units in a model zoo
Amil Dravid, Yossi Gandelsman, Alexei A. Efros, and Assaf Shocher · 2023
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Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
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CLIP-dissect: Automatic description of neuron representations in deep vision networks
Tuomas Oikarinen and Tsui-Wei Weng · 2023
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Dinov2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, et al · 2023
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Discover: making vision networks interpretable via competition and dissection
Konstantinos Panousis and Sotirios Chatzis · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
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Sigmoid loss for language image pre-training
Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, and Lucas Beyer · 2023
Cited alongside, same era.
Biomedgpt: A generalist vision-language foundation model for diverse biomedical tasks
Kai Zhang, Rong Zhou, Eashan Adhikarla, Zhiling Yan, Yixin Liu, Jun Yu, Zhengliang Liu, Xun Chen, Brian D. Davison, Hui Ren, Jing Huang, Chen Chen, Yuyin Zhou, Sunyang Fu, Wei Liu, Tianming Liu, Xiang Li, Yong Chen, Lifang He, James Zou, Quanzheng Li, Hongfang Liu, and Lichao Sun · 2023
Cited alongside, same era.
Refusal in language models is mediated by a single direction
Andy Arditi, Oscar Obeso, Aaquib Syed, Daniel Paleka, Nina Panickssery, Wes Gurnee, and Neel Nanda · 2024
Cited alongside, same era.
Interpreting clip with sparse linear concept embeddings (splice)
Usha Bhalla, Alex Oesterling, Suraj Srinivas, Flavio P Calmon, and Himabindu Lakkaraju · 2024
Cited alongside, same era.
Flair: Vlm with fine-grained language-informed image representations
Rui Xiao, Sanghwan Kim, Mariana-Iuliana Georgescu, Zeynep Akata, and Stephan Alaniz · 2024
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Sonicvisionlm: Playing sound with vision language models, 2024
Zhifeng Xie, Shengye Yu, Qile He, and Mengtian Li · 2024
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Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, et al · 2024
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Large multi-modal models can interpret features in large multi-modal models
Kaichen Zhang, Yifei Shen, Bo Li, and Ziwei Liu · 2024
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Bart Bussmann, Patrick Leask, and Neel Nanda · 2024
Cited alongside, same era.
Learning multi-level features with matryoshka saes
Bart Bussmann, Patrick Leask, and Neel Nanda · 2024
Cited alongside, same era.
Vision language models are few-shot audio spectrogram classifiers, 2024
Satvik Dixit, Laurie M. Heller, and Chris Donahue · 2024
Cited alongside, same era.
Evaluating feature steering: A case study in mitigating social biases, 2024
Esin Durmus, Alex Tamkin, Jack Clark, Jerry Wei, Jonathan Marcus, Joshua Batson, Kunal Handa, Liane Lovitt, Meg Tong, Miles McCain, Oliver Rausch, Saffron Huang, Sam Bowman, Stuart Ritchie, Tom Henighan, and Deep Ganguli · 2024
Cited alongside, same era.
Towards multimodal interpretability: Learning sparse interpretable features in vision transformers, April 2024
Hugo Fry · 2024
Cited alongside, same era.
Interpreting clip’s image representation via text-based decomposition
Yossi Gandelsman, Alexei A Efros, and Jacob Steinhardt · 2024
Cited alongside, same era.
Vision-language models for medical report generation and visual question answering: A review
Iryna Hartsock and Ghulam Rasool · 2024
Cited alongside, same era.
Vision-by-language for training-free compositional image retrieval
Shyamgopal Karthik, Karsten Roth, Massimiliano Mancini, and Zeynep Akata · 2024
Cited alongside, same era.
Dana Arad, Aaron Mueller, and Yonatan Belinkov · 2025
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Sub: Benchmarking cbm generalization via synthetic attribute substitutions
Jessica Bader, Leander Girrbach, Stephan Alaniz, and Zeynep Akata · 2025
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Stitch: Training-free position control in multimodal diffusion transformers
Jessica Bader, Mateusz Pach, Maria A Bravo, Serge Belongie, and Zeynep Akata · 2025
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Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders
Bartosz Cywiński and Kamil Deja · 2025
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Scaling language-free visual representation learning
David Fan, Shengbang Tong, Jiachen Zhu, Koustuv Sinha, Zhuang Liu, Xinlei Chen, Michael Rabbat, Nicolas Ballas, Yann LeCun, Amir Bar, and Saining Xie · 2025
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Multimodal autoregressive pre-training of large vision encoders
Enrico Fini, Mustafa Shukor, Xiujun Li, Philipp Dufter, Michal Klein, David Haldimann, Sai Aitharaju, Victor Guilherme Turrisi da Costa, Louis Béthune, Zhe Gan, Alexander T Toshev, Marcin Eichner, Moin Nabi, Yinfei Yang, Joshua M. Susskind, and Alaaeldin El-Nouby · 2025
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Interpreting the second-order effects of neurons in clip
Yossi Gandelsman, Alexei A Efros, and Jacob Steinhardt · 2025
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Scaling and evaluating sparse autoencoders
Leo Gao, Tom Dupre la Tour, Henk Tillman, Gabriel Goh, Rajan Troll, Alec Radford, Ilya Sutskever, Jan Leike, and Jeffrey Wu · 2025
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Rsgpt: A remote sensing vision language model and benchmark
Yuan Hu, Jianlong Yuan, Congcong Wen, Xiaonan Lu, Yu Liu, and Xiang Li · 2025
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A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions
Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, et al · 2025
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Analyzing finetuning representation shift for multimodal llms steering
Pegah Khayatan, Mustafa Shukor, Jayneel Parekh, Arnaud Dapogny, and Matthieu Cord · 2025
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Concept steerers: Leveraging k-sparse autoencoders for controllable generations
Dahye Kim and Deepti Ghadiyaram · 2025
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Introducing gpt-4.1 in the api, 2025
OpenAI · 2025
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Sparse autoencoders for scientifically rigorous interpretation of vision models
Samuel Stevens, Wei-Lun Chao, Tanya Berger-Wolf, and Yu Su · 2025
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Universal sparse autoencoders: Interpretable cross-model concept alignment
Harrish Thasarathan, Julian Forsyth, Thomas Fel, Matthew Kowal, and Konstantinos Derpanis · 2025
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The multi-faceted monosemanticity in multimodal representations
Hanqi Yan, Xiangxiang Cui, Lu Yin, Paul Pu Liang, Yulan He, and Yifei Wang · 2025
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