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ADIAS: Automated Design of Interactive Agentic Systems

Lekang Jiang, Bohan Tang, Stephan Goetz, Yiwen Guo · Aug 3, 2026

Citations: 0

Match reason: Matched by broad semantic/index fallback.

Score: 32% Sparse protocol signal Freshness: Warm Status: Fallback
Critique Edit General
  • Self-evolving agents can improve without updating model weights by iteratively optimizing the harness based on evaluation feedback.
  • On five interactive benchmarks, ADIAS outperforms the strongest baseline by 25.2% on average and achieves consistent gains across four backbone models.
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