11 citations · 24 across the 32 of their papers we have counts for
6 papers · 1 filter
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…
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…
SPIN: Sparsifying and Integrating Internal Neurons in Large Language Models for Text Classification
Difan Jiao, Yilun Liu, Zhenwei Tang +3
Among the many tasks that Large Language Models (LLMs) have revolutionized is text classification. Current text classification paradigms, however, rely solely on the output of the…
CoachLM: Automatic Instruction Revisions Improve the Data Quality in LLM Instruction Tuning
Yilun Liu, Shimin Tao, Xiaofeng Zhao +11
Instruction tuning is crucial for enabling Language Learning Models (LLMs) in responding to human instructions. The quality of instruction pairs used for tuning greatly affects the…
CaT: Balanced Continual Graph Learning with Graph Condensation
Yilun Liu, Ruihong Qiu, Zi Huang
Continual graph learning (CGL) is purposed to continuously update a graph model with graph data being fed in a streaming manner. Since the model easily forgets previously learned k…
Interpretable Online Log Analysis Using Large Language Models with Prompt Strategies
Yilun Liu, Shimin Tao, Weibin Meng +7
Automated log analysis is crucial in modern software-intensive systems for facilitating program comprehension throughout software maintenance and engineering life cycles. Existing…