Ximing Wen

GAProtoNet: A Multi-head Graph Attention-based Prototypical Network for Interpretable Text Classification

2024 · arXiv (Cornell University)

Pretrained transformer-based Language Models (LMs) are well-known for their ability to achieve significant improvement on text classification tasks with their powerful word embeddings, but their black-box nature, which leads to a lack of interpretability, has …

Language Model Meets Prototypes: Towards Interpretable Text Classification Models through Prototypical Networks

2024 · arXiv (Cornell University)

Pretrained transformer-based Language Models (LMs) are well-known for their ability to achieve significant improvement on NLP tasks, but their black-box nature, which leads to a lack of interpretability, has been a major concern. My dissertation …

Language Model Meets Prototypes: Towards Interpretable Text Classification Models through Prototypical Networks

2025 · Proceedings of the AAAI Conference on Artificial Intelligence

Pretrained transformer-based Language Models (LMs) are well-known for their ability to achieve significant improvement on NLP tasks, but their black-box nature, which leads to a lack of interpretability, has been a major concern. My dissertation …