PaperRegister: Boosting Flexible-grained Paper Search via Hierarchical Register Indexing

Li Zhuoqun, Xuanang Chen, Hongyu Lin, Yaojie Lu, Xianpei Han, Le Sun

PaperRegister: Boosting Flexible-grained Paper Search via Hierarchical Register Indexing: 23 upvotes on Hugging Face Daily Papers, #6 of 13 papers on 2025-08-18. Day-by-day upvote history.

Paper search is an important activity for researchers, typically involving using a query with description of a topic to find relevant papers. As research deepens, paper search requirements may become more flexible, sometimes involving specific details such as module configuration rather than being limited to coarse-grained topics. However, previous paper search systems are unable to meet these flexible-grained requirements, as these systems mainly collect paper abstracts to construct index of corpus, which lack detailed information to support retrieval by finer-grained queries. In this work, we propose PaperRegister, consisted of offline hierarchical indexing and online adaptive retrieval, transforming traditional abstract-based index into hierarchical index tree for paper search, thereby supporting queries at flexible granularity. Experiments on paper search tasks across a range of granularity demonstrate that PaperRegister achieves the state-of-the-art performance, and particularly excels in fine-grained scenarios, highlighting the good potential as an effective solution for flexible-grained paper search in real-world applications. Code for this work is in https://github.com/Li-Z-Q/PaperRegister.

Paper page on Hugging Face · arXiv

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