Expand arXiv paper corpus

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+# Paper: APPO: Agentic Procedural Policy Optimization
+
+---
+type: paper
+title: "APPO: Agentic Procedural Policy Optimization"
+authors: Xucong Wang, Ziyu Ma, Yong Wang, Yuxiang Ji, Shidong Yang, Guanhua Chen, Pengkun Wang, Xiangxiang Chu
+year: 2026
+venue: arXiv
+url: https://arxiv.org/abs/2606.12384
+code_url:
+source: arxiv
+collected_at: 2026-07-08
+published_at: 2026-06-10
+updated_at: 2026-06-10
+status: queued
+relevance: high
+topics:
+  - agent-evaluation
+  - tool-use
+  - workflow-agent
+methods:
+  -
+benchmarks:
+  -
+models:
+  -
+datasets:
+  - cs.LG
+  - cs.AI
+related_concepts:
+  -
+related_jobs:
+  -
+related_experiments:
+  -
+related_projects:
+  -
+collection_score: 14
+collection_queries: tool-use
+---
+
+## One-line Takeaway
+
+Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
+
+## Why Collected
+
+- matched queries: tool-use
+- inferred topics: agent-evaluation, tool-use, workflow-agent
+- arXiv categories: cs.LG, 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 `queued` to `skimmed` or `summarized`?
+
+## Links
+
+- arXiv: https://arxiv.org/abs/2606.12384