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Authors: Joshua Engels*, Callum McDougall*, Bilal Chughtai*, Janos Kramar, Senthoran Rajamanoharan, Cindy Wu, Arthur Conmy, Asic Q Chen, Jean Tarbouriech, Min Ma, Brendan O'Donoghue+, João Gabriel Lopes de Oliveira+, Rohin Shah+, Neel Nanda+ *Primary Contributor +Advising Paper here: https://arxiv.org/abs/2606.20560 Overview In a recent collaboration between the GDM interpretability team and...
This is the fourth in a series of informal research updates from the Google DeepMind Language Model Interpretability team, in interpretability and adjacent areas. The third post can be found here. Since SFT is the cause for many safety relevant properties, a natural strategy is to filter out rollouts from...
This is the third in a series of informal research updates from the Google DeepMind Language Model Interpretability team, in interpretability and adjacent areas. The second post can be found here. In this short post, we describe a surprising finding: most safety relevant properties in Gemini seem to be caused...
This is the second in a series of informal research updates from the Google DeepMind Language Model Interpretability team, in interpretability and adjacent areas. The first post can be found here. TL;DR * It is possible to build extremely simple agents that reliably find interesting behavioural differences between distinct models....
Authors: Daria Ivanova, Riya Tyagi, Josh Engels, Neel Nanda Daria and Riya are co-first authors. This work was done during Neel Nanda’s MATS 9.0. Claude helped write code and suggest edits for this post. Most of our tasks fall in 3 categories: predicting future actions, detecting the effect of an...
Code and data can be found here Executive Summary * We use data from Zhang et al. (2025) to measure LLM values. We find that our value metric can sometimes predict LLM behaviors on a test distribution in non-safety-relevant settings, but it is not super consistent. * In Zhang et...
This project is an extension of work done for Neel Nanda’s MATS 9.0 Training Phase. Neel Nanda and Josh Engels advised the project. Initial work on this project was done with David Vella Zarb. Thank you to Arya Jakkli, Paul Bogdan, and Monte MacDiarmid for providing feedback on the post...