SOTAVerified

Topic Models

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.

Papers

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Showing 1–50 of 881 papers

TitleStatusHype
Narrative Shift Detection: A Hybrid Approach of Dynamic Topic Models and Large Language ModelsCode0
Constrained Non-negative Matrix Factorization for Guided Topic Modeling of Minority TopicsCode0
topicwizard -- a Modern, Model-agnostic Framework for Topic Model Visualization and Interpretation—0
HAMLET: Healthcare-focused Adaptive Multilingual Learning Embedding-based Topic Modeling—0
Fully Bayesian Approaches to Topics over Time—0
Evaluating Negative Sampling Approaches for Neural Topic ModelsCode0
Multivariate Gaussian Topic Modelling: A novel approach to discover topics with greater semantic coherence—0
Seeded Poisson Factorization: Leveraging domain knowledge to fit topic modelsCode0
Unsupervised Topic Models are Data Mixers for Pre-training Language Models—0
Large Language Models Struggle to Describe the Haystack without Human Help: Human-in-the-loop Evaluation of LLMs—0
Hierarchical Graph Topic Modeling with Topic Tree-based Transformer—0
Exploring the Technology Landscape through Topic Modeling, Expert Involvement, and Reinforcement Learning—0
Visual Exploration of Stopword Probabilities in Topic Models—0
BERTopic for Topic Modeling of Hindi Short Texts: A Comparative Study—0
Detecting Neurocognitive Disorders through Analyses of Topic Evolution and Cross-modal Consistency in Visual-Stimulated Narratives—0
Analyzing Aviation Safety Narratives with LDA, NMF and PLSA: A Case Study Using Socrata Datasets—0
Bidirectional Topic Matching: Quantifying Thematic Overlap Between Corpora Through Topic Modelling—0
Enhancing Topic Interpretability for Neural Topic Modeling through Topic-wise Contrastive Learning—0
Refining Dimensions for Improving Clustering-based Cross-lingual Topic ModelsCode0
GloCOM: A Short Text Neural Topic Model via Global Clustering Context—0
Locating the Leading Edge of Cultural ChangeCode0
Provable unlearning in topic modeling and downstream tasks—0
Neural Topic Modeling with Large Language Models in the LoopCode1
From Word Vectors to Multimodal Embeddings: Techniques, Applications, and Future Directions For Large Language Models—0
Multi-environment Topic Models—0
Reliability of Topic ModelingCode0
Evolving Voices Based on Temporal Poisson Factorisation—0
Tethering Broken Themes: Aligning Neural Topic Models with Labels and Authors—0
Scalable Weibull Graph Attention Autoencoder for Modeling Document NetworksCode0
More than Memes: A Multimodal Topic Modeling Approach to Conspiracy Theories on Telegram—0
Enhancing Short-Text Topic Modeling with LLM-Driven Context Expansion and Prefix-Tuned VAEs—0
Embedded Topic Models Enhanced by Wikification—0
AutoTM 2.0: Automatic Topic Modeling Framework for Documents Analysis—0
NeuroMax: Enhancing Neural Topic Modeling via Maximizing Mutual Information and Group Topic Regularization—0
Investigating the Impact of Text Summarization on Topic Modeling—0
Iterative Improvement of an Additively Regularized Topic ModelCode1
Topic Modeling with Fine-tuning LLMs and Bag of SentencesCode0
Exchangeable Sequence Models Quantify Uncertainty Over Latent Concepts—0
TopicTag: Automatic Annotation of NMF Topic Models Using Chain of Thought and Prompt Tuning with LLMs—0
A Large-Scale Sensitivity Analysis on Latent Embeddings and Dimensionality Reductions for Text SpatializationsCode0
Text-to-Battery Recipe: A language modeling-based protocol for automatic battery recipe extraction and retrieval—0
Interactive Topic Models with Optimal Transport—0
Historia Magistra Vitae: Dynamic Topic Modeling of Roman Literature using Neural Embeddings—0
Cutting through the noise to motivate people: A comprehensive analysis of COVID-19 social media posts de/motivating vaccinationCode0
Determination of the Number of Topics Intrinsically: Is It Possible?Code1
S^3 -- Semantic Signal SeparationCode2
LLM Reading Tea Leaves: Automatically Evaluating Topic Models with Large Language ModelsCode0
RICo: Reddit ideological communitiesCode0
Comprehensive Evaluation of Large Language Models for Topic Modeling—0
FASTopic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic ModelCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1vONTSSC_v0.69—Unverified
2GSMC_v0.55—Unverified
3vNVDMC_v0.52—Unverified
4ETMC_v0.51—Unverified
5NSTMC_v0.38—Unverified
6ProdLDAC_v0.35—Unverified
#ModelMetricClaimedVerifiedStatus
1vONTSSC_v0.49—Unverified
2vNVDMC_v0.44—Unverified
3GSMC_v0.41—Unverified
4ETMC_v0.41—Unverified
5NSTMC_v0.37—Unverified
6ProdLDAC_v0.32—Unverified
#ModelMetricClaimedVerifiedStatus
1NVDMTest perplexity836—Unverified
2Bayesian SMMTest perplexity515—Unverified
#ModelMetricClaimedVerifiedStatus
1JoSHMACC83.24—Unverified
2TopicEqTopic Coherence@500.1—Unverified
#ModelMetricClaimedVerifiedStatus
1vONTSSC_v0.49—Unverified
#ModelMetricClaimedVerifiedStatus
1JoSHMACC90.91—Unverified