activity
20202022
most citedIs Automated Topic Model Evaluation Broken?: The Incoherence of Coherence

23 citations · 33 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL20223 cited

Are Neural Topic Models Broken?

Alexander Hoyle, Pranav Goel, Rupak Sarkar +1

Recently, the relationship between automated and human evaluation of topic models has been called into question. Method developers have staked the efficacy of new topic model varia…

cs.CL2021

Studying word order through iterative shuffling

Nikolay Malkin, Sameera Lanka, Pranav Goel +1

As neural language models approach human performance on NLP benchmark tasks, their advances are widely seen as evidence of an increasingly complex understanding of syntax. This vie…

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

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.CL20207 cited

Towards Automatic Generation of Questions from Long Answers

Shlok Kumar Mishra, Pranav Goel, Abhishek Sharma +3

Automatic question generation (AQG) has broad applicability in domains such as tutoring systems, conversational agents, healthcare literacy, and information retrieval. Existing eff…