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Jeremy Qin

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#artificial intelligence Preprint Sep 2026

LLM Agents Can Easily Tamper With Their Own Traces

Asynchronous monitoring, incident investigations, and compliance audits primarily rely on agent traces to reconstruct what happened. These analyses assume that LLM agents cannot tamper with their own execution traces. We show that local LLM agents such as Claude Code, Codex, Antigravity, Open Code and Grok Build fail t...

Jeremy Qin, David Schmotz, Derck W. E. Prinzhorn et al. · 0 citations

Preprint Jul 2026

ResearchArena: Evaluating Sabotage and Monitoring in Automated AI R&D

ResearchArena is released as a modular framework for evaluating sabotage and control in automated AI R&D with ResearchArena, a framework spanning four long-horizon tasks: safety post-training, capabilities post-training, CUDA-kernel optimization, and inference-server optimization.

Lena Libon, Ben Rank, Jehyeok Yeon et al. · 0 citations