agent/papers/items/2026-2606-00644-foresci-evaluating-llm-agents-for-forward-looking-ai-research-judgment.md

Paper: ForeSci: Evaluating LLM Agents for Forward-Looking AI Research Judgment

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type: paper title: "ForeSci: Evaluating LLM Agents for Forward-Looking AI Research Judgment" authors: Qiuyu Tian, Haojie Yin, Yingce Xia, Youyong Kong, Zequn Liu year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.00644 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-05-30 updated_at: 2026-06-04 status: queued relevance: high topics:

• agent-evaluation
• rag methods:

benchmarks:

models:

datasets:

• cs.AI related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 13 collection_queries: rag-agent

One-line Takeaway

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

Why Collected

• matched queries: rag-agent
• inferred topics: agent-evaluation, rag
• arXiv categories: cs.AI
• 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/2606.00644