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

TL;DR

PaperRegister introduces a hierarchical indexing method that significantly improves flexible-grained paper search, especially in fine-grained scenarios, by overcoming limitations of abstract-only indexing.

Contribution

It proposes a hierarchical index tree for paper search, enabling support for flexible granularity queries beyond traditional abstract-based methods.

Findings

Achieves state-of-the-art performance in paper search tasks.

Excels in fine-grained search scenarios.

Demonstrates potential for real-world applications.

Abstract

As researchers delve more deeply into their work, 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 previous systems mainly collect paper abstract to construct corpus index, which lacks detailed information to support retrieval by some finer-grained queries. In this work, we propose PaperRegister, which transforms traditional abstract-based index into a hierarchical index tree, thereby supporting queries at flexible granularity. Experiments on paper search tasks across a range of granularity demonstrate that PaperRegister achieves the SOTA performance, and particularly excels in the fine-grained scenarios, highlighting good potential as an effective solution for flexible-grained paper search in real-world applications. https://github.com/Li-Z-Q/PaperRegister.