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Topic Models
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A topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. Topic modeling is a frequently used text-mining tool for the discovery of hidden semantic structures in a text body.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Constrained Non-negative Matrix Factorization for Guided Topic Modeling of Minority Topics
topicwizard -- a Modern, Model-agnostic Framework for Topic Model Visualization and Interpretation
HAMLET: Healthcare-focused Adaptive Multilingual Learning Embedding-based Topic Modeling
Fully Bayesian Approaches to Topics over Time
How Large Language Models Are Changing MOOC Essay Answers: A Comparison of Pre- and Post-LLM Responses
Evaluating Negative Sampling Approaches for Neural Topic Models
Multivariate Gaussian Topic Modelling: A novel approach to discover topics with greater semantic coherence
DeFine: A Decomposed and Fine-Grained Annotated Dataset for Long-form Article Generation
QG-SMS: Enhancing Test Item Analysis via Student Modeling and Simulation
Seeded Poisson Factorization: Leveraging domain knowledge to fit topic models
ExpertGenQA: Open-ended QA generation in Specialized Domains
PinLanding: Content-First Keyword Landing Page Generation via Multi-Modal AI for Web-Scale Discovery
Unsupervised Topic Models are Data Mixers for Pre-training Language Models
Large Language Models Struggle to Describe the Haystack without Human Help: Human-in-the-loop Evaluation of LLMs
Hierarchical Graph Topic Modeling with Topic Tree-based Transformer
Exploring the Technology Landscape through Topic Modeling, Expert Involvement, and Reinforcement Learning
Visual Exploration of Stopword Probabilities in Topic Models
Detecting Neurocognitive Disorders through Analyses of Topic Evolution and Cross-modal Consistency in Visual-Stimulated Narratives
BERTopic for Topic Modeling of Hindi Short Texts: A Comparative Study
Analyzing Aviation Safety Narratives with LDA, NMF and PLSA: A Case Study Using Socrata Datasets
Bidirectional Topic Matching: Quantifying Thematic Overlap Between Corpora Through Topic Modelling
Enhancing Topic Interpretability for Neural Topic Modeling through Topic-wise Contrastive Learning
Refining Dimensions for Improving Clustering-based Cross-lingual Topic Models
GloCOM: A Short Text Neural Topic Model via Global Clustering Context
Locating the Leading Edge of Cultural Change
Provable unlearning in topic modeling and downstream tasks
Neural Topic Modeling with Large Language Models in the Loop
From Word Vectors to Multimodal Embeddings: Techniques, Applications, and Future Directions For Large Language Models
Multi-environment Topic Models
Reliability of Topic Modeling
Evolving Voices Based on Temporal Poisson Factorisation
Tethering Broken Themes: Aligning Neural Topic Models with Labels and Authors
Scalable Weibull Graph Attention Autoencoder for Modeling Document Networks
More than Memes: A Multimodal Topic Modeling Approach to Conspiracy Theories on Telegram
Enhancing Short-Text Topic Modeling with LLM-Driven Context Expansion and Prefix-Tuned VAEs
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