Author

Ming Jin

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#artificial intelligence Review Oct 2026

Groundability, Not Scale Alone: When Weak Reviewers Can Audit Strong Coding Agents

Coding agents can return plausible patches that omit required behavior. These failures are hard to review because long traces and confident summaries often hide what was missed. We ask when a nominally weaker reviewer can reliably decide whether a patch solves its issue. We study 411 execution-labeled traces from three...

Jun-Yu Guo, Shangding Gu, Ming Jin et al. · 0 citations

Jun 2026

Understanding and Evaluating Claw-like Agent Security Through a Computer-Systems Lens

SafeClawArena is developed, a benchmark of 406 adversarial tasks executed in containerized replicas of real agent platforms with canary-marked credentials and evaluated via automated taint tracking across nine output channels, exposing the inadequacy of current defenses and suggesting directions for future hardening.

Peizhi Niu, Wenjie Qu, Shangding Gu et al. · arXiv.org · 2 citations