agent/papers/items/2026-2607-21419-pats-policy-aware-training-scaffolding-for-agentic-reinforcement-learning.md

Paper: PATS: Policy-Aware Training Scaffolding for Agentic Reinforcement Learning

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type: paper title: "PATS: Policy-Aware Training Scaffolding for Agentic Reinforcement Learning" authors: Yipeng Shi, Zhipeng Ma, Yue Wang, Qitai Tan, Yang Li, Peng Chen, Zhengzhou Zhu year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.21419 code_url: source: arxiv collected_at: 2026-07-27 published_at: 2026-07-23 updated_at: 2026-07-23 status: queued relevance: high topics:

• agent-evaluation
• computer-use
• planning methods:

benchmarks:

models:

datasets:

• cs.AI related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 16 collection_queries: llm-agent

One-line Takeaway

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

Why Collected

• matched queries: llm-agent
• inferred topics: agent-evaluation, computer-use, planning
• arXiv categories: cs.AI
• collection score: 16

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/2607.21419