agent/papers/items/2025-2510-26167-toolrm-towards-agentic-tool-use-reward-modeling.md

Paper: ToolRM: Towards Agentic Tool-Use Reward Modeling

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type: paper title: "ToolRM: Towards Agentic Tool-Use Reward Modeling" authors: Renhao Li, Jianhong Tu, Yang Su, Yantao Liu, Fei Huang, Hamid Alinejad-Rokny, Derek F. Wong, Junyang Lin, et al. year: 2025 venue: arXiv url: https://arxiv.org/abs/2510.26167 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2025-10-30 updated_at: 2026-01-13 status: queued relevance: high topics:

• agent-evaluation
• tool-use methods:

benchmarks:

models:

datasets:

• cs.AI
• cs.CL related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 14 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, tool-use
• arXiv categories: cs.AI, cs.CL
• collection score: 14

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/2510.26167