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 151175 of 881 papers

TitleStatusHype
Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic ModelingCode0
Generative Topic Embedding: a Continuous Representation of DocumentsCode0
Comparative Evaluation of Label-Agnostic Selection Bias in Multilingual Hate Speech DatasetsCode0
Grammar induction from (lots of) words aloneCode0
Graph neural topic model with commonsense knowledgeCode0
Coherence-Aware Neural Topic ModelingCode0
Explainable and Discourse Topic-aware Neural Language UnderstandingCode0
Exploring conversation topics in conversational artificial intelligence–Based social mediated communities of practiceCode0
An Ontology-Based Recommender System with an Application to the Star Trek Television FranchiseCode0
Classifying Idiomatic and Literal Expressions Using Topic Models and Intensity of EmotionsCode0
Evaluating Topic Quality with Posterior VariabilityCode0
CATVI: Conditional and Adaptively Truncated Variational Inference for Hierarchical Bayesian Nonparametric ModelsCode0
Constrained Non-negative Matrix Factorization for Guided Topic Modeling of Minority TopicsCode0
Constrained Relational Topic ModelsCode0
Exploring Topic Coherence over Many Models and Many TopicsCode0
Construction and Quality Evaluation of Heterogeneous Hierarchical Topic ModelsCode0
Gaussian LDA for Topic Models with Word EmbeddingsCode0
Contextualized Topic Coherence MetricsCode0
ESTEEM: A Novel Framework for Qualitatively Evaluating and Visualizing Spatiotemporal Embeddings in Social MediaCode0
Discriminative Topic Mining via Category-Name Guided Text EmbeddingCode0
ETC-NLG: End-to-end Topic-Conditioned Natural Language GenerationCode0
Document Informed Neural Autoregressive Topic Models with Distributional PriorCode0
AOBTM: Adaptive Online Biterm Topic Modeling for Version Sensitive Short-texts AnalysisCode0
KATE: K-Competitive Autoencoder for TextCode0
Document Informed Neural Autoregressive Topic ModelsCode0
Show:102550
← PrevPage 7 of 36Next →

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