1.4 KiB
1.4 KiB
Paper: What Do AI Agents Actually Change? An Empirical Taxonomy of Mutation Patterns in Performance-Improving Pull Requests
type: paper title: What Do AI Agents Actually Change? An Empirical Taxonomy of Mutation Patterns in Performance-Improving Pull Requests authors: Illia Dovhoshliubnyi, Nima Soroush, Ashkan Sami, Alexander Brownlee year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.05666 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-07-06 updated_at: 2026-07-06 status: queued relevance: high topics:
- coding-agent methods:
benchmarks:
models:
datasets:
- cs.SE
- cs.AI related_concepts:
related_jobs:
related_experiments:
related_projects:
collection_score: 13 collection_queries: ai-agent, coding-agent
One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
Why Collected
- matched queries: ai-agent, coding-agent
- inferred topics: coding-agent
- arXiv categories: cs.SE, cs.AI
- collection score: 13
Review Checklist
- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
- Does it include a benchmark, dataset, code, or reproducible experimental setup?
- Should it be promoted from
queuedtoskimmedorsummarized?