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RubyLLM: A Ruby framework for all major AI providers
Ruby开发者福音！5分钟集成主流AI服务，支持问答、图像视频分析、文档总结等。
Article URL: https://rubyllm.com/ Comments URL: https://news.ycombinator.com/item?id=48660711 Points: 275 # Comments: 41
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Faithful by Construction: Claim-Anchored Attribution for Multi-Document Summarization
多文档摘要如何做到忠实可溯源？新方法让每条摘要声明都锚定原文依据，从构造上杜绝幻觉。
arXiv:2606.23989v1 Announce Type: cross Abstract: End-to-end large language models (LLMs) produce fluent multi-document summaries but remain prone to …
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EHRNote-ChatQA: A Benchmark for Evidence-Grounded Multi-Turn Clinical Question Answering over Longitudinal Discharge Summaries
面对长篇出院小结进行多轮查询时，Perplexity AI 能基于检索增强生成提供带来源的证据回答，助力医学专家高效合成病历信息。
arXiv:2606.15735v1 Announce Type: cross Abstract: Discharge summaries are crucial clinical documents containing the context of a patient's overall hos…
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A Training-Free Mixture-of-Agents Framework for Multi-Document Summarization using LLMs and Knowledge Graphs
提出无训练混合智能体框架，融合LLM与知识图谱，显著提升多文档摘要效率与质量。
arXiv:2606.03867v1 Announce Type: cross Abstract: Multi-Document Summarization (MDS) plays a critical role in distilling essential information from co…