arXiv cs.CL· Viswonathan Manoranjan, Taeyoon Kim, Nicholas Do, Sang Woo Kim, Dawei Li, Zhen Tan, Tianlong Chen, Yunmei Liu·· 13 小时前AI 评分27
ResearchHub：面向生物医学预印本的个性化文献发现系统
RESEARCHHUB: A Personalized Literature Discovery System for Biomedical Preprints
AI 导读
ResearchHub 是一个面向生物医学预印本的个性化文献发现系统，核心检索器 prism 在 44,937 篇 2023–2025 年 MedRxiv 论文上使 Recall@10 较 SPECTER2-Search 提升 12.4 个百分点。
正文 · 原文
Abstract:We present ResearchHub, an interactive system for personalized literature discovery over biomedical preprints. Given a researcher profile or a free-form query, ResearchHub retrieves relevant papers from a domain-specific MedRxiv corpus and helps users move beyond near-duplicate recommendations through controllable novelty, diversity, and curriculum ordering. At the core of the system is prism, a bi-encoder retriever adapted to biomedical preprints using GPT-4o-generated natural language queries and a hybrid Multiple Negatives Ranking plus MarginMSE objective with cross-encoder soft labels. On 44,937 MedRxiv papers from 2023--2025, prism outperforms strong off-the-shelf dense retrievers, improving Recall@10 over SPECTER2-Search by 12.4 percentage points. ResearchHub further supports frontier retrieval based on a user's reading history, DPP-based diversity re-ranking, Local Intrinsic Dimensionality ordering from mainstream to specialized papers, and lightweight attribution cards for result explanation. The full pipeline runs with low latency, making the system suitable
| Comments: | under-review |
| Subjects: | Information Retrieval (cs.IR); Computation and Language (cs.CL) |
| Cite as: | arXiv:2610.28636 [cs.IR] |
| (or arXiv:2610.28636v1 [cs.IR] for this version) | |
| https://doi.org/10.48550/arXiv.2610.28636 arXiv-issued DOI via DataCite |
Submission history
From: Dawei Li [view email]
[v1]
Wed, 5 Aug 2026 21:44:35 UTC (5,364 KB)
来源：arXiv cs.CL · arxiv.org