AI repair agents solve bugs more reliably when reports include executable reproduction scripts, file-level localization cues, and clear structure, while longer prose reports and human-oriented steps to reproduce show no benefit or hurt.
Humanevalcomm: Benchmarking the commu- nication competence of code generation for llms and llm agents
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LLM judges for human-AI coding co-creation show moderate performance (ROC-AUC 0.59) and low agreement, with co-creation success concentrating early in interactions.
citing papers explorer
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What Makes a Good Bug Report for an AI Agent?
AI repair agents solve bugs more reliably when reports include executable reproduction scripts, file-level localization cues, and clear structure, while longer prose reports and human-oriented steps to reproduce show no benefit or hurt.
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LLM-as-a-Judge for Human-AI Co-Creation: A Reliability-Aware Evaluation Framework for Coding
LLM judges for human-AI coding co-creation show moderate performance (ROC-AUC 0.59) and low agreement, with co-creation success concentrating early in interactions.