96 citations · 105 across the 12 of their papers we have counts for
6 papers · 1 filter
Controlled Crowdsourcing for High-Quality QA-SRL Annotation
Paul Roit, Ayal Klein, Daniela Stepanov +5
Question-answer driven Semantic Role Labeling (QA-SRL) was proposed as an attractive open and natural flavour of SRL, potentially attainable from laymen. Recently, a large-scale cr…
Yall should read this! Identifying Plurality in Second-Person Personal Pronouns in English Texts
Gabriel Stanovsky, Ronen Tamari
Distinguishing between singular and plural "you" in English is a challenging task which has potential for downstream applications, such as machine translation or coreference resolu…
On the Limits of Learning to Actively Learn Semantic Representations
Omri Koshorek, Gabriel Stanovsky, Yichu Zhou +2
One of the goals of natural language understanding is to develop models that map sentences into meaning representations. However, training such models requires expensive annotation…
Evaluating Gender Bias in Machine Translation
Gabriel Stanovsky, Noah A. Smith, Luke Zettlemoyer
We present the first challenge set and evaluation protocol for the analysis of gender bias in machine translation (MT). Our approach uses two recent coreference resolution datasets…
Gender trends in computer science authorship
Lucy Lu Wang, Gabriel Stanovsky, Luca Weihs +1
A large-scale, up-to-date analysis of Computer Science literature (11.8M papers through 2019) reveals that, if trends from the last 50 years continue, parity between the number of…
DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs
Dheeru Dua, Yizhong Wang, Pradeep Dasigi +3
Reading comprehension has recently seen rapid progress, with systems matching humans on the most popular datasets for the task. However, a large body of work has highlighted the br…