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SEABench: Benchmarking Endogenous Misalignment In Self-Evolving Agents
Self-evolving LLM agents have gained prominence for their ability to improve after deployment by modifying their harness, including their controller instructions, memory management protocols, and reusable tools and skills, in response to user and environment feedback. However, locally useful updates
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