140 citations · 411 across the 24 of their papers we have counts for
19 papers · 1 filter
Color Overmodification Emerges from Data-Driven Learning and Pragmatic Reasoning
Fei Fang, Kunal Sinha, Noah D. Goodman +2
Speakers' referential expressions often depart from communicative ideals in ways that help illuminate the nature of pragmatic language use. Patterns of overmodification, in which a…
Open-domain clarification question generation without question examples
Julia White, Gabriel Poesia, Robert Hawkins +2
An overarching goal of natural language processing is to enable machines to communicate seamlessly with humans. However, natural language can be ambiguous or unclear. In cases of u…
Calibrate your listeners! Robust communication-based training for pragmatic speakers
Rose E. Wang, Julia White, Jesse Mu +1
To be good conversational partners, natural language processing (NLP) systems should be trained to produce contextually useful utterances. Prior work has investigated training NLP…
Language Through a Prism: A Spectral Approach for Multiscale Language Representations
Alex Tamkin, Dan Jurafsky, Noah Goodman
Language exhibits structure at different scales, ranging from subwords to words, sentences, paragraphs, and documents. To what extent do deep models capture information at these sc…
Learning to refer informatively by amortizing pragmatic reasoning
Julia White, Jesse Mu, Noah D. Goodman
A hallmark of human language is the ability to effectively and efficiently convey contextually relevant information. One theory for how humans reason about language is presented in…
Investigating Transferability in Pretrained Language Models
Alex Tamkin, Trisha Singh, Davide Giovanardi +1
How does language model pretraining help transfer learning? We consider a simple ablation technique for determining the impact of each pretrained layer on transfer task performance…