agent/papers/items/2026-2607-09153-kv-prm-efficient-process-reward-modeling-via-kv-cache-transfer-for-multi-agent-t.md

Paper: KV-PRM: Efficient Process Reward Modeling via KV-Cache Transfer for Multi-Agent Test-Time Scaling

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type: paper title: "KV-PRM: Efficient Process Reward Modeling via KV-Cache Transfer for Multi-Agent Test-Time Scaling" authors: Peng Kuang, Haibo Jin, Xiaoyu Han, Yanli Wang, Xiaopeng Yuan, Ye Yu, Kaidi Xu, Haohan Wang year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.09153 code_url: source: arxiv collected_at: 2026-07-27 published_at: 2026-07-10 updated_at: 2026-07-10 status: queued relevance: high topics:

• agent-evaluation
• coding-agent
• computer-use
• memory
• multi-agent methods:

benchmarks:

models:

datasets:

• cs.AI related_concepts:

related_jobs:

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related_projects:

collection_score: 17 collection_queries: multi-agent-llm

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: multi-agent-llm
• inferred topics: agent-evaluation, coding-agent, computer-use, memory, multi-agent
• arXiv categories: cs.AI
• collection score: 17

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/2607.09153