Paper: Is Agentic Code Review Helpful? Mining Developers' Feedback to CodeRabbit Reviews in the Wild

type: paper title: "Is Agentic Code Review Helpful? Mining Developers' Feedback to CodeRabbit Reviews in the Wild" authors: Hong Yi Lin, Mingzhao Liang, Kla Tantithamthavorn, Patanamon Thongtanunam year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.03316 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-07-03 updated_at: 2026-07-03 status: queued relevance: high topics:

agent-safety
coding-agent
workflow-agent methods:

benchmarks:

models:

datasets:

cs.SE
cs.AI related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 13 collection_queries: autonomous-agent-llm

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

matched queries: autonomous-agent-llm
inferred topics: agent-safety, coding-agent, workflow-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 queued to skimmed or summarized?

1.4 KiB Raw Permalink Blame History