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Paper: PaperClaw: Harnessing Agents for Autonomous Research and Human-in-the-Loop Refinement


type: paper title: "PaperClaw: Harnessing Agents for Autonomous Research and Human-in-the-Loop Refinement" authors: Weiwei Ye, Hangchen Liu, Dongyuan Li, Renhe Jiang year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.22610 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-21 updated_at: 2026-06-21 status: queued relevance: high topics:

  • agent-evaluation
  • memory
  • multi-agent
  • tool-use methods:

benchmarks:

models:

datasets:

  • cs.AI related_concepts:

collection_score: 15 collection_queries: multi-agent-llm

One-line Takeaway

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

Why Collected

  • matched queries: multi-agent-llm
  • inferred topics: agent-evaluation, memory, multi-agent, tool-use
  • arXiv categories: cs.AI
  • collection score: 15

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?