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cs.LG2024
Multi-Label Bayesian Active Learning with Inter-Label Relationships
Yuanyuan Qi, Jueqing Lu, Xiaohao Yang +2
The primary challenge of multi-label active learning, differing it from multi-class active learning, lies in assessing the informativeness of an indefinite number of labels while a…
cs.CL2024
Neural Topic Modeling with Large Language Models in the Loop
Xiaohao Yang, He Zhao, Weijie Xu +4
Topic modeling is a fundamental task in natural language processing, allowing the discovery of latent thematic structures in text corpora. While Large Language Models (LLMs) have d…
cs.CL2024
LLM Reading Tea Leaves: Automatically Evaluating Topic Models with Large Language Models
Xiaohao Yang, He Zhao, Dinh Phung +2
Topic modeling has been a widely used tool for unsupervised text analysis. However, comprehensive evaluations of a topic model remain challenging. Existing evaluation methods are e…