BOUND refines LLMs' package-validity boundary via targeted editing to cut package hallucination rates by 79.9% on edit prompts and 65.4% on unseen prompts in recommendation tasks while generalizing to code generation.
Swe-bench: Can language models resolve real-world github issues?
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.SE 3years
2026 3representative citing papers
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.
AgentTether repairs 69% of initially failed LLM agent tasks on τ-bench by combining graph-guided root-cause diagnosis, cross-iteration repair memory, and guarded runtime intervention, improving over blind retry by 26 percentage points.
citing papers explorer
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Mitigating Package Hallucinations in Large Language Models via Model Editing
BOUND refines LLMs' package-validity boundary via targeted editing to cut package hallucination rates by 79.9% on edit prompts and 65.4% on unseen prompts in recommendation tasks while generalizing to code generation.
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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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AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation
AgentTether repairs 69% of initially failed LLM agent tasks on τ-bench by combining graph-guided root-cause diagnosis, cross-iteration repair memory, and guarded runtime intervention, improving over blind retry by 26 percentage points.