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Chronos framework enhances LLM code agents' reasoning over software evolution

By PulseAugur Editorial · [1 sources] ·

Researchers have developed Chronos, a new framework designed to help large language model (LLM)-based code agents reason about software evolution. Chronos distills historical pull requests into structured 'experience cards' and connects them via a graph of code, developer intent, and organizational relations. This allows semantic search to identify relevant changes, which are then retrieved through multi-hop expansion for selective reading. The framework guides agents in generating and selecting patches, showing significant improvements on benchmarks like SWE-Bench Verified, SWE-Bench Pro, and FEA-Bench Lite. AI

IMPACT Enhances LLM code agents' ability to understand and utilize historical code changes, potentially improving automated software development and maintenance.

RANK_REASON The cluster contains a research paper detailing a new framework for LLM code agents. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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

Chronos framework enhances LLM code agents' reasoning over software evolution

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The cluster contains a research paper detailing a new framework for LLM code agents. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Xin Yin, Yiang Zhang, Zhiyuan Peng, Chao Ni, Zhe Cui, Xiaohua Xin ·

    Chronos Enables Code Agents to Reason over Software Evolution

    arXiv:2610.11578v1 Announce Type: cross Abstract: Historical pull requests record the design decisions, compatibility constraints, and implementation patterns behind a codebase's current state. Experience relevant to a new task can span related changes whose descriptions emphasiz…

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