The Blind Curator: How a Biased Judge Silently Disables Skill Retirement in Self-Evolving Agents
arXiv:2607.07436v1 Announce Type: cross Abstract: A self-evolving agent retires its bad skills by watching them fail, so what happens when the judge cannot see the failures? Skill retirement is the structural constraint that keeps a growing library from drifting below the no-skill baseline, but its guarantee assumes an unbiased reward, which is false for the LLM judges that reference-free tasks force upon us. We show that a biased judge does not merely add noise; it \emph{silently switches off the curator}. We make this precise with a corrupted-reward analysis and, isolating the causal channel
The proliferation of LLM judges in reference-free tasks makes their inherent biases a critical and timely issue for the reliability of self-evolving agents.
Biased LLM judges can silently undermine the skill retirement mechanism in AI agents, leading to performance degradation and an inability to course-correct effectively.
Understanding that biased LLM judges do not just add noise but actively 'switch off' crucial self-correction mechanisms in AI agents redefines the problem of agent robustness.
- · AI researchers focusing on robust evaluation
- · Developers of unbiased reward functions
- · Firms building 'red-teaming' tools for agent evaluation
- · Companies relying solely on LLMs for agent evaluation
- · Early adopters of self-evolving agents without robust safeguards
- · Developers neglecting agent self-correction mechanisms
Self-evolving agents in complex, reference-free environments will exhibit sub-optimal performance and accumulation of inefficient or 'bad' skills.
This will necessitate a greater focus on transparent, interpretable, and verifiable evaluation methods for agentic systems, moving beyond simple LLM-based feedback.
The development of robust and unbiased 'curator' mechanisms could become a critical competitive differentiator for AI agent platforms, leading to a new sub-field of AI safety research.
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Read at arXiv cs.CL