Author

Jacob Steinhardt

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#artificial intelligence May 2025

Understanding In-context Learning of Addition via Activation Subspaces

A novel method is introduced that localizes the model's few-shot learning ability to only a few attention heads through dimensionality reduction and decomposition of the heads'output spaces, and derives a mathematical identity relating the''aggregator''and''extractor''subspaces of attention heads, allowing us to track...

Xin-Yang Hu, Kayo Yin, Michael I Jordan et al. · arXiv.org · 12 citations · ⚡2

Jul 2026

Norm Enforcement for AI Agents: Robustly Shaping Behavior in Multi-Agent Systems

It is found that simple enforcement mechanisms are exploited by misaligned agents for competitive advantage, even when they are not explicitly trained or prompted to do so, and mechanisms built on these principles resist exploitation, while still penalizing norm violations at comparable or lower cost than baselines.

Yaowen Ye, Jacob Steinhardt · arXiv.org · 1 citation