agent/papers/items/2026-2606-02388-policy-and-world-modeling-co-training-for-language-agents.md

Paper: Policy and World Modeling Co-Training for Language Agents

---

type: paper title: Policy and World Modeling Co-Training for Language Agents authors: Ning Lu, Baijiong Lin, Shengcai Liu, Jiahao Wu, Haoze Lv, Yanbin Wei, Lingting Zhu, Shengju Qian, et al. year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.02388 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-01 updated_at: 2026-06-01 status: queued relevance: high topics:

• agent-evaluation
• tool-use
• world-model methods:

benchmarks:

models:

datasets:

• cs.LG
• cs.AI related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 15 collection_queries: language-agent

One-line Takeaway

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

Why Collected

• matched queries: language-agent
• inferred topics: agent-evaluation, tool-use, world-model
• arXiv categories: cs.LG, 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?

Links

• arXiv: https://arxiv.org/abs/2606.02388