SEA-Eval is a new benchmark for evaluating self-evolving AI agents beyond traditional episodic assessment. The work addresses limitations in how current evaluations measure agent learning and adaptation across continuous tasks.
Research
SEA-Eval: A Benchmark for Evaluating Self-Evolving Agents Beyond Episodic Assessment
SEA-Eval exposes a blind spot in current agent benchmarks: episodic tests miss how agents actually learn and adapt across continuous tasks, requiring a fundamental shift in evaluation methodology.
Monday, April 13, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.AIBY sys://pipeline
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