11 papers
Leveraging Hierarchical Taxonomies in Prompt-based Continual Learning
Quyen Tran, Hoang Phan, Minh Le +6
Humans perceive the world as a series of sequential events, which can be hierarchically organized with different levels of abstraction based on conceptual knowledge. Drawing inspir…
CoT2Align: Cross-Chain of Thought Distillation via Optimal Transport Alignment for Language Models with Different Tokenizers
Anh Duc Le, Tu Vu, Nam Le Hai +4
Large Language Models (LLMs) achieve state-of-the-art performance across various NLP tasks but face deployment challenges due to high computational costs and memory constraints. Kn…
Few-Shot, No Problem: Descriptive Continual Relation Extraction
Nguyen Xuan Thanh, Anh Duc Le, Quyen Tran +3
Few-shot Continual Relation Extraction is a crucial challenge for enabling AI systems to identify and adapt to evolving relationships in dynamic real-world domains. Traditional mem…
Few-shot Continual Relation Extraction via Open Information Extraction
Thiem Nguyen, Anh Nguyen, Quyen Tran +4
Typically, Few-shot Continual Relation Extraction (FCRE) models must balance retaining prior knowledge while adapting to new tasks with extremely limited data. However, real-world…
GloCOM: A Short Text Neural Topic Model via Global Clustering Context
Quang Duc Nguyen, Tung Nguyen, Duc Anh Nguyen +3
Uncovering hidden topics from short texts is challenging for traditional and neural models due to data sparsity, which limits word co-occurrence patterns, and label sparsity, stemm…
ToVo: Toxicity Taxonomy via Voting
Tinh Son Luong, Thanh-Thien Le, Thang Viet Doan +3
Existing toxic detection models face significant limitations, such as lack of transparency, customization, and reproducibility. These challenges stem from the closed-source nature…