most citedCross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing

11 citations · 11 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CL2020

Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning

Roei Schuster, Tal Schuster, Yoav Meri +1

Word embeddings, i.e., low-dimensional vector representations such as GloVe and SGNS, encode word "meaning" in the sense that distances between words' vectors correspond to their s…

cs.CL2019

Automatic Fact-guided Sentence Modification

Darsh J Shah, Tal Schuster, Regina Barzilay

Online encyclopediae like Wikipedia contain large amounts of text that need frequent corrections and updates. The new information may contradict existing content in encyclopediae.…

cs.CL2019

Towards Debiasing Fact Verification Models

Tal Schuster, Darsh J Shah, Yun Jie Serene Yeo +3

Fact verification requires validating a claim in the context of evidence. We show, however, that in the popular FEVER dataset this might not necessarily be the case. Claim-only cla…

cs.CL2019

The Limitations of Stylometry for Detecting Machine-Generated Fake News

Tal Schuster, Roei Schuster, Darsh J Shah +1

Recent developments in neural language models (LMs) have raised concerns about their potential misuse for automatically spreading misinformation. In light of these concerns, severa…

cs.CL201911 cited

Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing

Tal Schuster, Ori Ram, Regina Barzilay +1

We introduce a novel method for multilingual transfer that utilizes deep contextual embeddings, pretrained in an unsupervised fashion. While contextual embeddings have been shown t…