Author

Daniele Bonadiman

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Review Oct 2026

Peer Pressure: Execution-Verified Co-Evolution of Attacker and Defender Populations for Code Security

LLM code agents increasingly ship code with little oversight, yet defenders trained on static vulnerability datasets fall behind adapting adversaries. We co-train attacker and defender instead, and let execution decide every reward: an attacker (Red) edits a real repository and earns nothing unless its patch applies, b...

Khushbu Pahwa, Yu-Bin Ge, Daniele Bonadiman et al. · 0 citations

#artificial intelligence Preprint Oct 2026

Plan-and-Patch: Diffusion Language Models for Agentic Planning

Planning is increasingly important for long-horizon agents, where successful execution requires coordinating subgoals, tool use, and intermediate outcomes over many steps. Yet assumptions made during planning may be invalidated by the environment, tools may return unexpected results, or actions may fail. Effective agen...

Syamantak Kumar, Jiang Guo, Hassan Hamad et al. · 0 citations