agent/papers/items/2026-2606-27483-internalizing-the-future-a-unified-agentic-training-paradigm-for-world-model-pla.md

Paper: Internalizing the Future: A Unified Agentic Training Paradigm for World Model Planning

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type: paper title: "Internalizing the Future: A Unified Agentic Training Paradigm for World Model Planning" authors: Xuan Zhang, Zhijian Zhou, Lingfeng Qiao, Yulei Qin, Ke Li, Xing Sun, Xiaoyu Tan, Chao Qu, et al. year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.27483 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-25 updated_at: 2026-06-25 status: queued relevance: high topics:

• agent-evaluation
• planning
• rag
• reasoning
• world-model methods:

benchmarks:

models:

datasets:

• cs.AI related_concepts:

related_jobs:

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related_projects:

collection_score: 16 collection_queries: planning-agent

One-line Takeaway

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

Why Collected

• matched queries: planning-agent
• inferred topics: agent-evaluation, planning, rag, reasoning, world-model
• 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/2606.27483