agent/papers/items/2026-2607-08894-gats-graph-augmented-tree-search-with-layered-world-models-for-efficient-agent-p.md

Paper: GATS: Graph-Augmented Tree Search with Layered World Models for Efficient Agent Planning

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type: paper title: "GATS: Graph-Augmented Tree Search with Layered World Models for Efficient Agent Planning" authors: Maureese Williams, Dymitr Nowicki year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.08894 code_url: source: arxiv collected_at: 2026-07-27 published_at: 2026-07-09 updated_at: 2026-07-09 status: queued relevance: high topics:

• coding-agent
• computer-use
• embodied-agent
• planning
• tool-use
• workflow-agent
• world-model methods:

benchmarks:

models:

datasets:

• cs.AI related_concepts:

related_jobs:

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related_projects:

collection_score: 16 collection_queries: language-agent, planning-agent

One-line Takeaway

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

Why Collected

• matched queries: language-agent, planning-agent
• inferred topics: coding-agent, computer-use, embodied-agent, planning, tool-use, workflow-agent, 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/2607.08894