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agent/papers/items/2026-2602-14234-redsearcher-a-scalable-and-cost-efficient-framework-for-long-horizon-search-agen.md
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# Paper: REDSearcher: A Scalable and Cost-Efficient Framework for Long-Horizon Search Agents
---
type: paper
title: "REDSearcher: A Scalable and Cost-Efficient Framework for Long-Horizon Search Agents"
authors: Zheng Chu, Xiao Wang, Jack Hong, Huiming Fan, Yuqi Huang, Yue Yang, Guohai Xu, Chenxiao Zhao, et al.
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2602.14234
code_url:
source: arxiv
collected_at: 2026-07-08
published_at: 2026-02-15
updated_at: 2026-02-15
status: queued
relevance: high
topics:
- agent-evaluation
- planning
- rag
- tool-use
methods:
-
benchmarks:
-
models:
-
datasets:
- cs.AI
- cs.CL
related_concepts:
-
related_jobs:
-
related_experiments:
-
related_projects:
-
collection_score: 13
collection_queries: function-calling
---
## One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
## Why Collected
- matched queries: function-calling
- inferred topics: agent-evaluation, planning, rag, tool-use
- arXiv categories: cs.AI, cs.CL
- collection score: 13
## 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/2602.14234