wuyang
1.3 KiB
1.3 KiB
Paper: Who&When Pro: Can LLMs Really Attribute Failures in AI Agents?
type: paper title: "Who&When Pro: Can LLMs Really Attribute Failures in AI Agents?" authors: Jiale Liu, Huajun Xi, Shaokun Zhang, Yifan Zeng, Tianwei Yue, Chi Wang, Jian Kang, Qingyun Wu, et al. year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.09996 code_url: source: arxiv collected_at: 2026-07-27 published_at: 2026-07-10 updated_at: 2026-07-10 status: queued relevance: high topics:
- agent-evaluation
- computer-use methods:
benchmarks:
models:
datasets:
- cs.AI related_concepts:
related_jobs:
related_experiments:
related_projects:
collection_score: 14 collection_queries: ai-agent
One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
Why Collected
- matched queries: ai-agent
- inferred topics: agent-evaluation, computer-use
- arXiv categories: cs.AI
- collection score: 14
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?