1 citations · 1 across the 2 of their papers we have counts for
3 papers
An Attention-Based Model for Predicting Contextual Informativeness and Curriculum Learning Applications
Sungjin Nam, David Jurgens, Gwen Frishkoff +1
Both humans and machines learn the meaning of unknown words through contextual information in a sentence, but not all contexts are equally helpful for learning. We introduce an eff…
Human Perception of Surprise: A User Study
Nalin Chhibber, Rohail Syed, Mengqiu Teng +3
Understanding how to engage users is a critical question in many applications. Previous research has shown that unexpected or astonishing events can attract user attention, leading…
Predicting the Relative Difficulty of Single Sentences With and Without Surrounding Context
Elliot Schumacher, Maxine Eskenazi, Gwen Frishkoff +1
The problem of accurately predicting relative reading difficulty across a set of sentences arises in a number of important natural language applications, such as finding and curati…