activity
20192021
most citedIs Automated Topic Model Evaluation Broken?: The Incoherence of Coherence

23 citations · 28 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL202123 cited

Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherence

Alexander Hoyle, Pranav Goel, Denis Peskov +3

Topic model evaluation, like evaluation of other unsupervised methods, can be contentious. However, the field has coalesced around automated estimates of topic coherence, which rel…

cs.CL2020

Promoting Graph Awareness in Linearized Graph-to-Text Generation

Alexander Hoyle, Ana Marasović, Noah Smith

Generating text from structured inputs, such as meaning representations or RDF triples, has often involved the use of specialized graph-encoding neural networks. However, recent ap…

cs.CL2020

Improving Neural Topic Models using Knowledge Distillation

Alexander Hoyle, Pranav Goel, Philip Resnik

Topic models are often used to identify human-interpretable topics to help make sense of large document collections. We use knowledge distillation to combine the best attributes of…

cs.CL2019

Unsupervised Discovery of Gendered Language through Latent-Variable Modeling

Alexander Hoyle, Wolf-Sonkin, Hanna Wallach +2

Studying the ways in which language is gendered has long been an area of interest in sociolinguistics. Studies have explored, for example, the speech of male and female characters…

cs.CL20195 cited

Combining Sentiment Lexica with a Multi-View Variational Autoencoder

Alexander Hoyle, Lawrence Wolf-Sonkin, Hanna Wallach +2

When assigning quantitative labels to a dataset, different methodologies may rely on different scales. In particular, when assigning polarities to words in a sentiment lexicon, ann…