1 citations · 1 across the 24 of their papers we have counts for
5 papers · 2 filters
WAVE++: Capturing Within-Task Variance for Continual Relation Extraction with Adaptive Prompting
Bao-Ngoc Dao, Minh Le, Quang Nguyen +3
Memory-based approaches have shown strong performance in Continual Relation Extraction (CRE). However, storing examples from previous tasks increases memory usage and raises privac…
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…
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…
Adaptive Prompting for Continual Relation Extraction: A Within-Task Variance Perspective
Minh Le, Tien Ngoc Luu, An Nguyen The +5
To address catastrophic forgetting in Continual Relation Extraction (CRE), many current approaches rely on memory buffers to rehearse previously learned knowledge while acquiring n…