9 papers
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…
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…
Text Meets Topology: Rethinking Out-of-distribution Detection in Text-Rich Networks
Danny Wang, Ruihong Qiu, Guangdong Bai +1
Out-of-distribution (OOD) detection remains challenging in text-rich networks, where textual features intertwine with topological structures. Existing methods primarily address lab…
ALSA: Anchors in Logit Space for Out-of-Distribution Accuracy Estimation
Chenzhi Liu, Mahsa Baktashmotlagh, Yanran Tang +2
Estimating model accuracy on unseen, unlabeled datasets is crucial for real-world machine learning applications, especially under distribution shifts that can degrade performance.…
UQLegalAI@COLIEE2025: Advancing Legal Case Retrieval with Large Language Models and Graph Neural Networks
Yanran Tang, Ruihong Qiu, Zi Huang
Legal case retrieval plays a pivotal role in the legal domain by facilitating the efficient identification of relevant cases, supporting legal professionals and researchers to prop…
GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation
Danny Wang, Ruihong Qiu, Guangdong Bai +1
Despite graph neural networks' (GNNs) great success in modelling graph-structured data, out-of-distribution (OOD) test instances still pose a great challenge for current GNNs. One…