activity
20232026
most citedPUMA: Efficient Continual Graph Learning for Node Classification with Graph Condensation

1 citations · 1 across the 9 of their papers we have counts for

collaborators

10 papers

cs.IR2026

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…

cs.AI2026

Call Neighbours Yourself: Graph Walks with Destination-Conditioned On-Policy Self-Distillation

Yilun Liu, Boyu Luo, Yanran Tang +2

Reasoning over text-attributed graphs (TAGs) requires large language models (LLMs) to combine a node's text with evidence distributed across its neighbourhood. Existing methods fix…

cs.IR2025

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…

cs.LG2025

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.…

cs.IR2025

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…

cs.IR2024

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…

cs.IR2024

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…

cs.IR2023

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…

cs.LG2023★ 1 cited

PUMA: Efficient Continual Graph Learning for Node Classification with Graph Condensation

Yilun Liu, Ruihong Qiu, Yanran Tang +2

When handling streaming graphs, existing graph representation learning models encounter a catastrophic forgetting problem, where previously learned knowledge of these models is eas…

cs.IR2023

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…