agent/papers/items/2026-2601-12988-paperguide-making-small-language-model-paper-reading-agents-more-efficient.md

Paper: PaperGuide: Making Small Language-Model Paper-Reading Agents More Efficient

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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