87 citations · 136 across the 11 of their papers we have counts for
30 papers · 1 filter
Modeling Event Plausibility with Consistent Conceptual Abstraction
Ian Porada, Kaheer Suleman, Adam Trischler +1
Understanding natural language requires common sense, one aspect of which is the ability to discern the plausibility of events. While distributional models -- most recently pre-tra…
The Topic Confusion Task: A Novel Scenario for Authorship Attribution
Malik H. Altakrori, Jackie Chi Kit Cheung, Benjamin C. M. Fung
Authorship attribution is the problem of identifying the most plausible author of an anonymous text from a set of candidate authors. Researchers have investigated same-topic and cr…
Deep Discourse Analysis for Generating Personalized Feedback in Intelligent Tutor Systems
Matt Grenander, Robert Belfer, Ekaterina Kochmar +3
We explore creating automated, personalized feedback in an intelligent tutoring system (ITS). Our goal is to pinpoint correct and incorrect concepts in student answers in order to…
On-the-Fly Attention Modulation for Neural Generation
Yue Dong, Chandra Bhagavatula, Ximing Lu +4
Despite considerable advancements with deep neural language models (LMs), neural text generation still suffers from degeneration: the generated text is repetitive, generic, self-co…
Optimizing Deeper Transformers on Small Datasets
Peng Xu, Dhruv Kumar, Wei Yang +6
It is a common belief that training deep transformers from scratch requires large datasets. Consequently, for small datasets, people usually use shallow and simple additional layer…
Deconstructing word embedding algorithms
Kian Kenyon-Dean, Edward Newell, Jackie Chi Kit Cheung
Word embeddings are reliable feature representations of words used to obtain high quality results for various NLP applications. Uncontextualized word embeddings are used in many NL…