Swabha Swayamdipta

Publications
Influence

Annotation Artifacts in Natural Language Inference Data

Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel R. Bowman, Noah A. Smith
Computer Science
NAACL-HLT
6 March 2018

Large-scale datasets for natural language inference are created by presenting crowd workers with a sentence (premise), and asking them to generate three new sentences (hypotheses) that it entails, contradicts, or is logically neutral with respect to. Expand

DyNet: The Dynamic Neural Network Toolkit

Graham Neubig, Chris Dyer, +22 authors Pengcheng Yin
Computer Science, Mathematics
ArXiv
15 January 2017

We describe DyNet, a toolkit for implementing neural network models based on dynamic declaration of network structure. Expand

Don't Stop Pretraining: Adapt Language Models to Domains and Tasks

Suchin Gururangan, Ana Marasović, +4 authors Noah A. Smith
Computer Science
ACL
23 April 2020

We present a study across four domains (biomedical and computer science publications, news, and reviews) and eight classification tasks, showing that a second phase of pretraining in-domain (domain-adaptive pretraining) leads to performance gains, under both high- and low-resource settings. Expand

A Dependency Parser for Tweets

Lingpeng Kong, Nathan Schneider, Swabha Swayamdipta, Archna Bhatia, Chris Dyer, Noah A. Smith
Computer Science
EMNLP
1 October 2014

We describe TWEEBOPARSER, a dependency parser for English tweets that achieves over 80% unlabeled attachment score on a new, high-quality test set. Expand

Frame-Semantic Parsing with Softmax-Margin Segmental RNNs and a Syntactic Scaffold

Swabha Swayamdipta, Sam Thomson, Chris Dyer, Noah A. Smith
Computer Science
ArXiv
29 June 2017

We present a new, efficient frame-semantic parser that labels semantic arguments to FrameNet predicates. Expand

Syntactic Scaffolds for Semantic Structures

Swabha Swayamdipta, Sam Thomson, Kenton Lee, Luke Zettlemoyer, Chris Dyer, Noah A. Smith
Computer Science
EMNLP
30 August 2018

We introduce the syntactic scaffold, an approach to incorporating syntactic information into semantic tasks. Expand

Adversarial Filters of Dataset Biases

Ronan Le Bras, Swabha Swayamdipta, +4 authors Yejin Choi
Computer Science, Mathematics
ICML
10 February 2020

We investigate one recently proposed approach, AFLite, which adversarially filters such dataset biases, as a means to mitigate the prevalent overestimation of machine performance. Expand

Greedy, Joint Syntactic-Semantic Parsing with Stack LSTMs

Swabha Swayamdipta, Miguel Ballesteros, Chris Dyer, Noah A. Smith
Computer Science
CoNLL
29 June 2016

We present a transition-based parser that jointly produces syntactic and semantic dependencies. Expand

Learning Joint Semantic Parsers from Disjoint Data

Hao Peng, Sam Thomson, Swabha Swayamdipta, Noah A. Smith
Computer Science
NAACL-HLT
17 April 2018

We present a new approach to learning semantic parsers from multiple datasets, even when the target semantic formalisms are drastically different, and the underlying corpora do not overlap. Expand

Transfer Learning in Natural Language Processing

Sebastian Ruder, Matthew E. Peters, Swabha Swayamdipta, Thomas Wolf
Computer Science
NAACL-HLT
1 June 2019

We present an overview of modern transfer learning methods in NLP, how models are pre-trained, what information the representations they learn capture, and review examples and case studies on how these models can be integrated and adapted in downstream NLP tasks. Expand

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