5 citations · 13 across the 14 of their papers we have counts for
7 papers · 1 filter
Collaborative Cognitive Diagnosis with Disentangled Representation Learning for Learner Modeling
Weibo Gao, Qi Liu, Linan Yue +4
Learners sharing similar implicit cognitive states often display comparable observable problem-solving performances. Leveraging collaborative connections among such similar learner…
Towards Few-shot Self-explaining Graph Neural Networks
Jingyu Peng, Qi Liu, Linan Yue +3
Recent advancements in Graph Neural Networks (GNNs) have spurred an upsurge of research dedicated to enhancing the explainability of GNNs, particularly in critical domains such as…
Empowering Few-Shot Relation Extraction with The Integration of Traditional RE Methods and Large Language Models
Ye Liu, Kai Zhang, Aoran Gan +4
Few-Shot Relation Extraction (FSRE), a subtask of Relation Extraction (RE) that utilizes limited training instances, appeals to more researchers in Natural Language Processing (NLP…
Event Grounded Criminal Court View Generation with Cooperative (Large) Language Models
Linan Yue, Qi Liu, Lili Zhao +3
With the development of legal intelligence, Criminal Court View Generation has attracted much attention as a crucial task of legal intelligence, which aims to generate concise and…
Cooperative Classification and Rationalization for Graph Generalization
Linan Yue, Qi Liu, Ye Liu +3
Graph Neural Networks (GNNs) have achieved impressive results in graph classification tasks, but they struggle to generalize effectively when faced with out-of-distribution (OOD) d…
Towards Faithful Explanations: Boosting Rationalization with Shortcuts Discovery
Linan Yue, Qi Liu, Yichao Du +3
The remarkable success in neural networks provokes the selective rationalization. It explains the prediction results by identifying a small subset of the inputs sufficient to suppo…
Communication-Efficient Personalized Federated Learning for Speech-to-Text Tasks
Yichao Du, Zhirui Zhang, Linan Yue +5
To protect privacy and meet legal regulations, federated learning (FL) has gained significant attention for training speech-to-text (S2T) systems, including automatic speech recogn…