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Found 5 papers, 1 papers with code
Learning How To Learn NLP: Developing Introductory Concepts Through Scaffolded Discovery
We present a scaffolded discovery learning approach to introducing concepts in a Natural Language Processing course aimed at computer science students at liberal arts institutions.
More Than Words: Collocation Retokenization for Latent Dirichlet Allocation Models
Traditionally, Latent Dirichlet Allocation (LDA) ingests words in a collection of documents to discover their latent topics using word-document co-occurrences.
More Than Words: Collocation Tokenization for Latent Dirichlet Allocation Models
Traditionally, Latent Dirichlet Allocation (LDA) ingests words in a collection of documents to discover their latent topics using word-document co-occurrences.
How effective is BERT without word ordering? Implications for language understanding and data privacy
Ordered word sequences contain the rich structures that define language.
Locally Private Bayesian Inference for Count Models
We present a general method for privacy-preserving Bayesian inference in Poisson factorization, a broad class of models that includes some of the most widely used models in the social sciences.
