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agent/papers/items/2026-2601-12988-paperguide-making-small-language-model-paper-reading-agents-more-efficient.md
2026-07-08 12:25:30 +08:00

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# Paper: PaperGuide: Making Small Language-Model Paper-Reading Agents More Efficient
---
type: paper
title: "PaperGuide: Making Small Language-Model Paper-Reading Agents More Efficient"
authors: Zijian Wang, Tiancheng Huang, Hanqi Li, Da Ma, Lu Chen, Kai Yu
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2601.12988
code_url:
source: arxiv
collected_at: 2026-07-08
published_at: 2026-01-19
updated_at: 2026-01-19
status: queued
relevance: high
topics:
- agent-evaluation
- computer-use
- planning
- reasoning
- tool-use
methods:
-
benchmarks:
-
models:
-
datasets:
- cs.LG
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, computer-use, planning, reasoning, tool-use
- arXiv categories: cs.LG
- 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/2601.12988