agent/papers/items/2026-2607-06273-agenttether-graph-guided-diagnosis-and-runtime-intervention-for-reliable-llm-age.md

Paper: AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation

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type: paper title: "AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation" authors: Chenyu Zhao, Shenglin Zhang, Wenwei Gu, Yongqian Sun, Dan Pei, Chetan Bansal, Saravan Rajmohan, Minghua Ma year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.06273 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-07-07 updated_at: 2026-07-07 status: queued relevance: high topics:

• agent-evaluation
• computer-use
• memory
• reasoning
• tool-use methods:

benchmarks:

models:

datasets:

• cs.SE related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 17 collection_queries: llm-agent, tool-use

One-line Takeaway

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

Why Collected

• matched queries: llm-agent, tool-use
• inferred topics: agent-evaluation, computer-use, memory, reasoning, tool-use
• arXiv categories: cs.SE
• collection score: 17

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/2607.06273