Self-Reports Are Not Verification: Environment-Grounded Auditing of LLM Operators in Evolutionary Search

arXiv:2609.00652 · cs.AI, cs.LG, cs.NE · Submitted 2026-09-01 · Read on arXiv

cs.AI, cs.LG, cs.NE

Submitted: 2026-09-01

Updated: 2026-09-01

Terminology

• Calibration — 32× in this paper · explained in 7 episodes
• Accuracy — 21× in this paper · explained in 1 episode
• Verification — 11× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Agent Architectures — 1× in this paper · explained in 1 episode
• Agentic Loop — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• LLM judge — 1× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Provenance — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• Language Models (Mostly) Know What They Know
• Measuring Faithfulness in Chain-of-Thought Reasoning
• Evolution through Large Models
• Let's Verify Step by Step
• Evolutionary Computation in the Era of Large Language Model: Survey and Roadmap

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