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News/SEAGym: An Evaluation Environment for Self-Evolving LLM Agents
arxiv
PublishedJune 17, 2026 at 4:00 AM
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SEAGym: An Evaluation Environment for Self-Evolving LLM Agents

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arXiv:2606.17546v1 Announce Type: new Abstract: Self-evolving LLM-based agents improve mainly by changing their agent harness: the structured execution layer around a base model, including prompts, memory, tools, middleware, runtime state, and the model-tool interaction loop. Existing evaluations of

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