2 citations · 3 across the 6 of their papers we have counts for
6 papers
XTRA: Cross-Lingual Topic Modeling with Topic and Representation Alignments
Tien Phat Nguyen, Vu Minh Ngo, Tung Nguyen +4
Cross-lingual topic modeling aims to uncover shared semantic themes across languages. Several methods have been proposed to address this problem, leveraging both traditional and ne…
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…
NeuroMax: Enhancing Neural Topic Modeling via Maximizing Mutual Information and Group Topic Regularization
Duy-Tung Pham, Thien Trang Nguyen Vu, Tung Nguyen +3
Recent advances in neural topic models have concentrated on two primary directions: the integration of the inference network (encoder) with a pre-trained language model (PLM) and t…
Memorization-Dilation: Modeling Neural Collapse Under Label Noise
Duc Anh Nguyen, Ron Levie, Julian Lienen +2
The notion of neural collapse refers to several emergent phenomena that have been empirically observed across various canonical classification problems. During the terminal phase o…
Central-Smoothing Hypergraph Neural Networks for Predicting Drug-Drug Interactions
Duc Anh Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
Predicting drug-drug interactions (DDI) is the problem of predicting side effects (unwanted outcomes) of a pair of drugs using drug information and known side effects of many pairs…
A Rate-Distortion Framework for Explaining Black-box Model Decisions
Stefan Kolek, Duc Anh Nguyen, Ron Levie +2
We present the Rate-Distortion Explanation (RDE) framework, a mathematically well-founded method for explaining black-box model decisions. The framework is based on perturbations o…