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Multi-agent LLM system Phoenix automates GitHub issue resolution

By PulseAugur Editorial · [1 sources] ·

Researchers have developed Phoenix, a multi-agent LLM system designed to automatically resolve GitHub issues. The system utilizes six specialized agents, including a planner, coder, and tester, to manage the process from issue triage to pull request creation. Phoenix incorporates seven layered safety controls and a baseline-aware testing strategy, achieving a 75% oracle resolution rate on a curated SWE-bench Lite slice and maintaining 100% correctness preservation in a pilot study on real-world issues. AI

IMPACT This research demonstrates a significant step towards autonomous software development and maintenance, potentially streamlining developer workflows.

RANK_REASON The cluster describes a research paper detailing a novel system for automated issue resolution using LLMs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Multi-agent LLM system Phoenix automates GitHub issue resolution

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The cluster describes a research paper detailing a novel system for automated issue resolution using LLMs. [lever_c_demoted from research: ic=1 ai=1.0]
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paper, product, safety
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88 days old
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COVERAGE [1]

  1. arXiv cs.MA (Multiagent) TIER_1 (CA) · Joao Barros ·

    Phoenix: Safe GitHub Issue Resolution via Multi-Agent LLMs

    We present Phoenix, a multi-agent LLM system that resolves GitHub issues from triage through pull-request creation, combining seven layered safety controls with a baseline-aware test evaluation strategy. Phoenix decomposes the work across six specialized agents. Planner, reproduc…

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