agent/papers/items/2026-2605-13542-realicu-do-llm-agents-understand-long-context-icu-data-a-benchmark-beyond-behavi.md

Paper: RealICU: Do LLM Agents Understand Long-Context ICU Data? A Benchmark Beyond Behavior Imitation

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type: paper title: "RealICU: Do LLM Agents Understand Long-Context ICU Data? A Benchmark Beyond Behavior Imitation" authors: Chengzhi Shen, Weixiang Shen, Tobias Susetzky, Chen, Chen, Jun Li, Yuyuan Liu, Xuepeng Zhang, et al. year: 2026 venue: arXiv url: https://arxiv.org/abs/2605.13542 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-05-13 updated_at: 2026-05-13 status: queued relevance: high topics:

• agent-evaluation
• agent-safety
• memory
• planning
• reasoning
• tool-use methods:

benchmarks:

models:

datasets:

• cs.AI
• cs.CL
• cs.LG
• cs.MA related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 20 collection_queries: agent-memory

One-line Takeaway

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

Why Collected

• matched queries: agent-memory
• inferred topics: agent-evaluation, agent-safety, memory, planning, reasoning, tool-use
• arXiv categories: cs.AI, cs.CL, cs.LG, cs.MA
• collection score: 20

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/2605.13542