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篇活跃论文
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周度回顾
把还没处理完的 backlog、连续逾期、周期复查回归和已完成论文拆开，帮助你把每天的变化提醒沉淀成周度研究推进视图。
周期复查
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篇论文
周度回顾
日级提醒只推新的行动变化，周报则把 backlog、连续逾期和周期复查统一收口。
已过期
这些论文已经超过计划处理日期，应该在本周优先清理。
Weekly Review
标星Paper Circle: An Open-source Multi-agent Research Discovery and Analysis Framework
The rapid growth of scientific literature has made it increasingly difficult for researchers to efficiently discover, evaluate, and synthesize relevant work. Recent advances in multi-agent large language models (LLMs) h…
备注：Anchor paper for the multi-agent discovery workflow; compare its planner design with newer agent benchmarks.
下一步：compare planner design with newer agent benchmarks
最晚处理：2026-04-18
Weekly Review
待跟进ClinicRealm: Re-evaluating large language models with conventional machine learning for non-generative clinical prediction tasks.
Large Language Models (LLMs) are increasingly deployed in medicine. However, their utility for non-generative clinical prediction is under-evaluated, and they are often assumed to be inferior to specialized models, crea…
备注：Recheck whether ClinicRealm still beats classical clinical baselines under the same task framing.
下一步：recheck benchmark framing against classical baselines
最晚处理：2026-04-20
复查周期：每 14 天
还没处理完的
所有仍在 star、follow_up 或 reading 阶段的活跃 backlog，适合作为本周持续推进清单。
Weekly Review
标星Paper Circle: An Open-source Multi-agent Research Discovery and Analysis Framework
The rapid growth of scientific literature has made it increasingly difficult for researchers to efficiently discover, evaluate, and synthesize relevant work. Recent advances in multi-agent large language models (LLMs) h…
备注：Anchor paper for the multi-agent discovery workflow; compare its planner design with newer agent benchmarks.
下一步：compare planner design with newer agent benchmarks
最晚处理：2026-04-18
Weekly Review
待跟进ClinicRealm: Re-evaluating large language models with conventional machine learning for non-generative clinical prediction tasks.
Large Language Models (LLMs) are increasingly deployed in medicine. However, their utility for non-generative clinical prediction is under-evaluated, and they are often assumed to be inferior to specialized models, crea…
备注：Recheck whether ClinicRealm still beats classical clinical baselines under the same task framing.
下一步：recheck benchmark framing against classical baselines
最晚处理：2026-04-20
复查周期：每 14 天
已连续逾期的
这些论文已经持续逾期，应该从 backlog 里优先清理或重新安排。
Weekly Review
标星Paper Circle: An Open-source Multi-agent Research Discovery and Analysis Framework
The rapid growth of scientific literature has made it increasingly difficult for researchers to efficiently discover, evaluate, and synthesize relevant work. Recent advances in multi-agent large language models (LLMs) h…
备注：Anchor paper for the multi-agent discovery workflow; compare its planner design with newer agent benchmarks.
下一步：compare planner design with newer agent benchmarks
最晚处理：2026-04-18
Weekly Review
待跟进ClinicRealm: Re-evaluating large language models with conventional machine learning for non-generative clinical prediction tasks.
Large Language Models (LLMs) are increasingly deployed in medicine. However, their utility for non-generative clinical prediction is under-evaluated, and they are often assumed to be inferior to specialized models, crea…
备注：Recheck whether ClinicRealm still beats classical clinical baselines under the same task framing.
下一步：recheck benchmark framing against classical baselines
最晚处理：2026-04-20
复查周期：每 14 天