Extracting latent steering vectors from pretrained language models, 2022
Nishant Subramani, Nivedita Suresh, and Matthew E. Peters · 2022
Cited alongside, same era.
Eliciting latent predictions from transformers with the tuned lens, 2023
Nora Belrose, Zach Furman, Logan Smith, Danny Halawi, Igor Ostrovsky, Lev McKinney, Stella Biderman, and Jacob Steinhardt · 2023
Cited alongside, same era.
Pythia: A suite for analyzing large language models across training and scaling, 2023
Stella Biderman, Hailey Schoelkopf, Quentin Anthony, Herbie Bradley, Kyle O’Brien, Eric Hallahan, Mohammad Aflah Khan, Shivanshu Purohit, USVSN Sai Prashanth, Edward Raff, Aviya Skowron, Lintang Sutawika, and Oskar van der Wal · 2023
Cited alongside, same era.
Language models can explain neurons in language models
Steven Bills, Nick Cammarata, Dan Mossing, Henk Tillman, Leo Gao, Gabriel Goh, Ilya Sutskever, Jan Leike, Jeff Wu, and William Saunders · 2023
Cited alongside, same era.
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, Robert Lasenby, Yifan Wu, Shauna Kravec, Nicholas Schiefer, Tim Maxwell, Nicholas Joseph, Zac Hatfield-Dodds, Alex Tamkin, Karina Nguyen, Brayden McLean, Josiah E Burke, Tristan Hume, Shan Carter, Tom Henighan, and Christopher Olah · 2023
Cited alongside, same era.
A toy model of universality: Reverse engineering how networks learn group operations, 2023
Original
Bilal Chughtai, Lawrence Chan, and Neel Nanda · 2023
Cited alongside, same era.
Towards automated circuit discovery for mechanistic interpretability, 2023
Arthur Conmy, Augustine N. Mavor-Parker, Aengus Lynch, Stefan Heimersheim, and Adrià Garriga-Alonso · 2023
Cited alongside, same era.
Sparse autoencoders find highly interpretable features in language models, 2023
Hoagy Cunningham, Aidan Ewart, Logan Riggs, Robert Huben, and Lee Sharkey · 2023
Cited alongside, same era.
Generalizing backpropagation for gradient-based interpretability, 2023
Kevin Du, Lucas Torroba Hennigen, Niklas Stoehr, Alexander Warstadt, and Ryan Cotterell · 2023
Cited alongside, same era.
Localizing model behavior with path patching, 2023
Nicholas Goldowsky-Dill, Chris MacLeod, Lucas Sato, and Aryaman Arora · 2023
Cited alongside, same era.
Finding neurons in a haystack: Case studies with sparse probing, 2023
Wes Gurnee, Neel Nanda, Matthew Pauly, Katherine Harvey, Dmitrii Troitskii, and Dimitris Bertsimas · 2023
Cited alongside, same era.
How does gpt-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model, 2023
Michael Hanna, Ollie Liu, and Alexandre Variengien · 2023
Cited alongside, same era.