Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback. - Rohin Shah; Steven H. Wang; Cody Wild; Stephanie Milani; Anssi Kanervisto; Vinicius G. Goecks; Nicholas R. Waytowich; David Watkins-Valls; Bharat Prakash; Edmund Mills; Divyansh Garg; Alexander Fries; et al. (NeurIPS (Competition and Demos), 2021)

Retrospective on the 2021 BASALT Competition on Learning from Human Feedback. - Rohin Shah; Steven H. Wang; Cody Wild; Stephanie Milani; Anssi Kanervisto; Vinicius G. Goecks; Nicholas R. Waytowich; David Watkins-Valls; Bharat Prakash; Edmund Mills; Divyansh Garg; Alexander Fries; et al. (CoRR, 2022)

Progress measures for grokking via mechanistic interpretability. - Neel Nanda; Lawrence Chan; Tom Lieberum; Jess Smith; Jacob Steinhardt (ICLR, 2023)

Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla. - Tom Lieberum; Matthew Rahtz; János Kramár; Neel Nanda; Geoffrey Irving; Rohin Shah; Vladimir Mikulik (CoRR, 2023)

Improving Sparse Decomposition of Language Model Activations with Gated Sparse Autoencoders. - Senthooran Rajamanoharan; Arthur Conmy; Lewis Smith; Tom Lieberum; Vikrant Varma; János Kramár; Rohin Shah; Neel Nanda (NeurIPS, 2024)

AtP*: An efficient and scalable method for localizing LLM behaviour to components. - János Kramár; Tom Lieberum; Rohin Shah; Neel Nanda (CoRR, 2024)

Evaluating Frontier Models for Dangerous Capabilities. - Mary Phuong; Matthew Aitchison; Elliot Catt; Sarah Cogan; Alexandre Kaskasoli; Victoria Krakovna; David Lindner; Matthew Rahtz; Yannis Assael; Sarah Hodkinson; Heidi Howard; Tom Lieberum; et al. (CoRR, 2024)

Improving Dictionary Learning with Gated Sparse Autoencoders. - Senthooran Rajamanoharan; Arthur Conmy; Lewis Smith; Tom Lieberum; Vikrant Varma; János Kramár; Rohin Shah; Neel Nanda (CoRR, 2024)

Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders. - Senthooran Rajamanoharan; Tom Lieberum; Nicolas Sonnerat; Arthur Conmy; Vikrant Varma; János Kramár; Neel Nanda (CoRR, 2024)

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 D. Dragan; Rohin Shah; Neel Nanda (CoRR, 2024)