agent/papers/items/2026-2606-02497-bridging-the-last-mile-of-time-series-forecasting-with-llm-agents.md

Paper: Bridging the Last Mile of Time Series Forecasting with LLM Agents

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type: paper title: Bridging the Last Mile of Time Series Forecasting with LLM Agents authors: Yuhua Liao, Zetian Wang, Qiangqiang Nie, Zhenhua Zhang year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.02497 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-safety
• memory
• planning
• reasoning
• tool-use methods:

benchmarks:

models:

datasets:

• cs.AI related_concepts:

related_jobs:

related_experiments:

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-safety, memory, planning, reasoning, tool-use
• 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/2606.02497