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QuoteBench: How Matched Scores Can Hide Command-Path Failures
arXiv cs.AI · Published · 3 min read
In 30 seconds
- What happened
- QuoteBench reveals that LLM coding agents' matched execution scores hide failures introduced during command serialization and parsing, not generation.
- Why it matters
- Engineers evaluating or deploying LLM-based command-issuing agents need to understand how execution transport affects real-world success rates.
- Watch out
- A model's matched score can mask up to 64 points of damage offset by 60 points of compensation, making rankings unstable across deployment configurations.
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