6 papers
Cassette: Case-to-Case Structural Distillation for Efficient Legal Case Retrieval
Yanran Tang, Ruihong Qiu, Hongzhi Yin +2
Legal case retrieval (LCR) is an essential tool for not only assisting legal practitioners to efficiently retrieve precedents but also enabling ordinary individuals to find valuabl…
ReaKase-8B: Legal Case Retrieval via Knowledge and Reasoning Representations with LLMs
Yanran Tang, Ruihong Qiu, Xue Li +1
Legal case retrieval (LCR) is a cornerstone of real-world legal decision making, as it enables practitioners to identify precedents for a given query case. Existing approaches main…
LEXA: Legal Case Retrieval via Graph Contrastive Learning with Contextualised LLM Embeddings
Yanran Tang, Ruihong Qiu, Yilun Liu +2
Legal case retrieval (LCR) is a specialised information retrieval task aimed at identifying relevant cases given a query case. LCR holds pivotal significance in facilitating legal…
CaseLink: Inductive Graph Learning for Legal Case Retrieval
Yanran Tang, Ruihong Qiu, Hongzhi Yin +2
In case law, the precedents are the relevant cases that are used to support the decisions made by the judges and the opinions of lawyers towards a given case. This relevance is ref…
CaseGNN: Graph Neural Networks for Legal Case Retrieval with Text-Attributed Graphs
Yanran Tang, Ruihong Qiu, Yilun Liu +2
Legal case retrieval is an information retrieval task in the legal domain, which aims to retrieve relevant cases with a given query case. Recent research of legal case retrieval ma…
Prompt-based Effective Input Reformulation for Legal Case Retrieval
Yanran Tang, Ruihong Qiu, Xue Li
Legal case retrieval plays an important role for legal practitioners to effectively retrieve relevant cases given a query case. Most existing neural legal case retrieval models dir…