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 226–250 of 881 papers

TitleStatusHype
EvaLDA: Efficient Evasion Attacks Towards Latent Dirichlet AllocationCode0
TAN-NTM: Topic Attention Networks for Neural Topic Modeling—0
Developing a Curated Topic Model for COVID-19 Medical Research Literature—0
Improved Topic Representations of Medical Documents to Assist COVID-19 Literature Exploration—0
Semi-Supervised Topic Modeling for Gender Bias Discovery in English and Swedish—0
Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network—0
Topic modelling discourse dynamics in historical newspapers—0
TOMODAPI: A Topic Modeling API to Train, Use and Compare Topic ModelsCode1
Which Matters Most? Comparing the Impact of Concept and Document Relationships in Topic Models—0
Rethinking Topic Modelling: From Document-Space to Term-Space—0
Short Text Topic Modeling with Topic Distribution Quantization and Negative Sampling DecoderCode1
Learning VAE-LDA Models with Rounded Reparameterization Trick—0
Comparative Evaluation of Label-Agnostic Selection Bias in Multilingual Hate Speech DatasetsCode0
Friendly Topic Assistant for Transformer Based Abstractive Summarization—0
TopicModel4J: A Java Package for Topic ModelsCode1
Topic Modeling with Contextualized Word Representation Clusters—0
Helping users discover perspectives: Enhancing opinion mining with joint topic models—0
On a Guided Nonnegative Matrix FactorizationCode0
A Disentangled Adversarial Neural Topic Model for Separating Opinions from Plots in User ReviewsCode0
Weakly-Supervised Aspect-Based Sentiment Analysis via Joint Aspect-Sentiment Topic EmbeddingCode1
Paying down metadata debt: learning the representation of concepts using topic models—0
Improving Neural Topic Models using Knowledge DistillationCode1
Unification of HDP and LDA Models for Optimal Topic Clustering of Subject Specific Question Banks—0
AOBTM: Adaptive Online Biterm Topic Modeling Method for Version Sensitive Short-texts AnalysisCode0
A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect DetectionCode1
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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