collaborators

11 papers

cs.AI2026

Mind Viruses: Self-Propagating Ideas in Multi-Agent LLM Systems

Vassilis Papadopoulos, McNair Shah, Sam Zimmerman +1

AI agents are becoming more autonomous and increasingly interconnected, exposing them to new emergent risks arising from agent-to-agent interaction. One such risk is the spread of…

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.LG2026

Mechanisms of Introspective Awareness

Uzay Macar, Li Yang, Atticus Wang +3

Recent work has shown that LLMs can sometimes detect when steering vectors are injected into their residual stream and identify the injected concept -- a phenomenon termed "introsp…

cs.AI2026

SAE-StatSteer: Statistical Consensus Feature Selection for Optimization-Free Activation Steering of Large Language Models

Oshayer Siddique, J. M Areeb Uzair Alam, Md Jobayer Rahman Rafy +3

Activation steering adds a residual-stream direction at inference time, providing lightweight behavioral control without fine-tuning. Sparse autoencoders (SAEs) can make such inter…

cs.AI2026

Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet

Adly Templeton, Tom Conerly, Jonathan Marcus +23

We demonstrate that sparse autoencoders can extract interpretable features from Claude 3 Sonnet, a production-scale language model, addressing the open question of whether dictiona…