most citedFinding the Law: Enhancing Statutory Article Retrieval via Graph Neural Networks

3 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024

Know When to Fuse: Investigating Non-English Hybrid Retrieval in the Legal Domain

Antoine Louis, Gijs van Dijck, Gerasimos Spanakis

Hybrid search has emerged as an effective strategy to offset the limitations of different matching paradigms, especially in out-of-domain contexts where notable improvements in ret…

cs.CL20242 cited

ColBERT-XM: A Modular Multi-Vector Representation Model for Zero-Shot Multilingual Information Retrieval

Antoine Louis, Vageesh Saxena, Gijs van Dijck +1

State-of-the-art neural retrievers predominantly focus on high-resource languages like English, which impedes their adoption in retrieval scenarios involving other languages. Curre…

cs.CL2023

IDTraffickers: An Authorship Attribution Dataset to link and connect Potential Human-Trafficking Operations on Text Escort Advertisements

Vageesh Saxena, Benjamin Bashpole, Gijs Van Dijck +1

Human trafficking (HT) is a pervasive global issue affecting vulnerable individuals, violating their fundamental human rights. Investigations reveal that a significant number of HT…

cs.CL20232 cited

Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models

Antoine Louis, Gijs van Dijck, Gerasimos Spanakis

Many individuals are likely to face a legal dispute at some point in their lives, but their lack of understanding of how to navigate these complex issues often renders them vulnera…

cs.IR20233 cited

Finding the Law: Enhancing Statutory Article Retrieval via Graph Neural Networks

Antoine Louis, Gijs van Dijck, Gerasimos Spanakis

Statutory article retrieval (SAR), the task of retrieving statute law articles relevant to a legal question, is a promising application of legal text processing. In particular, hig…