Shangao Li

Published on Aug 13 · Submitted by lsamc on Aug 21 Abstract QuoteBench reveals that execution-boundary parsing errors significantly reduce LLM coding agent success, and disclosing the boundary helps recover performance, showing that evaluation must account for deployment configuration rather than treating matched scores as intrinsic model properties. LLM coding agents issue Bash commands through interfaces that may serialize, wrap, and reparse model output.