collaborators

5 papers

cs.CL2026

Verbalizable Representations Form a Global Workspace in Language Models

Wes Gurnee, Nicholas Sofroniew, Adam Pearce +13

Out of everything the human brain processes, only a small fraction is consciously accessible, in the sense of being available for verbal report, deliberate control, and flexible re…

cs.CL2026

The Value Axis: Language Models Encode Whether They're on the Right Track

Nick Jiang, Isaac Kauvar, Jack Lindsey

We investigate whether language models internally track the value of their current trajectory, defined as the likelihood that their ongoing strategy will achieve their goals. Using…

cs.AI2026

Emotion Concepts and their Function in a Large Language Model

Nicholas Sofroniew, Isaac Kauvar, William Saunders +13

Large language models (LLMs) sometimes appear to exhibit emotional reactions. We investigate why this is the case in Claude Sonnet 4.5 and explore implications for alignment-releva…

cs.LG2026

When Models Manipulate Manifolds: The Geometry of a Counting Task

Wes Gurnee, Emmanuel Ameisen, Isaac Kauvar +4

Language models can perceive visual properties of text despite receiving only sequences of tokens-we mechanistically investigate how Claude 3.5 Haiku accomplishes one such task: li…

cs.LG2024

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning

Miles Hutson, Isaac Kauvar, Nick Haber

Model-based reinforcement learning (MBRL) is a promising route to sample-efficient policy optimization. However, a known vulnerability of reconstruction-based MBRL consists of scen…