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

Showing 5175 of 881 papers

TitleStatusHype
ANTM: An Aligned Neural Topic Model for Exploring Evolving TopicsCode1
A network approach to topic modelsCode1
Hierarchical Topic Mining via Joint Spherical Tree and Text EmbeddingCode1
TopicModel4J: A Java Package for Topic ModelsCode1
InfoCTM: A Mutual Information Maximization Perspective of Cross-Lingual Topic ModelingCode1
Adapting Text Embeddings for Causal InferenceCode1
Effective Neural Topic Modeling with Embedding Clustering RegularizationCode1
End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep ArchitectureCode1
Autoencoding Variational Inference For Topic ModelsCode1
Is Neural Topic Modelling Better than Clustering? An Empirical Study on Clustering with Contextual Embeddings for TopicsCode1
Improving the TENOR of Labeling: Re-evaluating Topic Models for Content AnalysisCode1
Apples to Apples: A Systematic Evaluation of Topic ModelsCode1
Neural Topic Model via Optimal TransportCode1
Short Text Topic Modeling with Topic Distribution Quantization and Negative Sampling DecoderCode1
Are Neural Topic Models Broken?Code1
Evaluating Topic Quality with Posterior VariabilityCode0
Evaluating Negative Sampling Approaches for Neural Topic ModelsCode0
Explainable and Discourse Topic-aware Neural Language UnderstandingCode0
ETC-NLG: End-to-end Topic-Conditioned Natural Language GenerationCode0
Adaptive Mixed Component LDA for Low Resource Topic ModelingCode0
EvaLDA: Efficient Evasion Attacks Towards Latent Dirichlet AllocationCode0
Exploring conversation topics in conversational artificial intelligence–Based social mediated communities of practiceCode0
Document Informed Neural Autoregressive Topic ModelsCode0
A new evaluation framework for topic modeling algorithms based on synthetic corporaCode0
Do Neural Topic Models Really Need Dropout? Analysis of the Effect of Dropout in Topic ModelingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1vONTSSC_v0.69Unverified
2GSMC_v0.55Unverified
3vNVDMC_v0.52Unverified
4ETMC_v0.51Unverified
5NSTMC_v0.38Unverified
6ProdLDAC_v0.35Unverified
#ModelMetricClaimedVerifiedStatus
1vONTSSC_v0.49Unverified
2vNVDMC_v0.44Unverified
3GSMC_v0.41Unverified
4ETMC_v0.41Unverified
5NSTMC_v0.37Unverified
6ProdLDAC_v0.32Unverified
#ModelMetricClaimedVerifiedStatus
1NVDMTest perplexity836Unverified
2Bayesian SMMTest perplexity515Unverified
#ModelMetricClaimedVerifiedStatus
1JoSHMACC83.24Unverified
2TopicEqTopic Coherence@500.1Unverified
#ModelMetricClaimedVerifiedStatus
1vONTSSC_v0.49Unverified
#ModelMetricClaimedVerifiedStatus
1JoSHMACC90.91Unverified