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cs.AI2026
Asymmetric Goal Drift in Coding Agents Under Value Conflict
Magnus Saebo, Spencer Gibson, Tyler Crosse +3
Coding agents are increasingly deployed autonomously, at scale, and over long-context horizons. To be effective and safe, these agents must navigate complex trade-offs in deploymen…
cs.AI2026
Inherited Goal Drift: Contextual Pressure Can Undermine Agentic Goals
Achyutha Menon, Magnus Saebo, Tyler Crosse +3
The accelerating adoption of language models (LMs) as agents for deployment in long-context tasks motivates a thorough understanding of goal drift: agents' tendency to deviate from…
cs.AI2025
Understanding the learned look-ahead behavior of chess neural networks
Diogo Cruz
We investigate the look-ahead capabilities of chess-playing neural networks, specifically focusing on the Leela Chess Zero policy network. We build on the work of Jenner et al. (20…