Swabha Swayamdipta

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Carnegie Mellon University ∙ University of Washington ∙ Allen Institute for Artificial Intelligence

G-DAUG: Generative Data Augmentation for Commonsense Reasoning

Recent advances in commonsense reasoning depend on large-scale human-ann...
04/24/2020 ∙ by Yiben Yang, et al. ∙ 0 ∙ share

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

Language models pretrained on text from a wide variety of sources form t...
04/23/2020 ∙ by Suchin Gururangan, et al. ∙ 0 ∙ share

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The Right Tool for the Job: Matching Model and Instance Complexities

As NLP models become larger, executing a trained model requires signific...
04/16/2020 ∙ by Roy Schwartz, et al. ∙ 0 ∙ share

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Adversarial Filters of Dataset Biases

Large neural models have demonstrated human-level performance on languag...
02/10/2020 ∙ by Ronan Le Bras, et al. ∙ 14 ∙ share

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Shallow Syntax in Deep Water

Shallow syntax provides an approximation of phrase-syntactic structure o...
08/29/2019 ∙ by Swabha Swayamdipta, et al. ∙ 0 ∙ share

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Syntactic Scaffolds for Semantic Structures

We introduce the syntactic scaffold, an approach to incorporating syntac...
08/30/2018 ∙ by Swabha Swayamdipta, et al. ∙ 0 ∙ share

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Polyglot Semantic Role Labeling

Previous approaches to multilingual semantic dependency parsing treat la...
05/29/2018 ∙ by Phoebe Mulcaire, et al. ∙ 0 ∙ share

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Learning Joint Semantic Parsers from Disjoint Data

We present a new approach to learning semantic parsers from multiple dat...
04/17/2018 ∙ by Hao Peng, et al. ∙ 0 ∙ share

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Annotation Artifacts in Natural Language Inference Data

Large-scale datasets for natural language inference are created by prese...
03/06/2018 ∙ by Suchin Gururangan, et al. ∙ 0 ∙ share

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Multi-Mention Learning for Reading Comprehension with Neural Cascades

Reading comprehension is a challenging task, especially when executed ac...
11/02/2017 ∙ by Swabha Swayamdipta, et al. ∙ 0 ∙ share

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

We present a new, efficient frame-semantic parser that labels semantic a...
06/29/2017 ∙ by Swabha Swayamdipta, et al. ∙ 0 ∙ share

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DyNet: The Dynamic Neural Network Toolkit

We describe DyNet, a toolkit for implementing neural network models base...
01/15/2017 ∙ by Graham Neubig, et al. ∙ 0 ∙ share

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Greedy, Joint Syntactic-Semantic Parsing with Stack LSTMs

We present a transition-based parser that jointly produces syntactic and...
06/29/2016 ∙ by Swabha Swayamdipta, et al. ∙ 0 ∙ share

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Swabha Swayamdipta

Featured Co-authors

Graham Neubig

Noah A. Smith

Yoav Goldberg

Chris Dyer

Luke Zettlemoyer

Yejin Choi

Samuel R. Bowman

Trevor Cohn

Hao Peng

Ashish Sabharwal

Kevin Duh

G-DAUG: Generative Data Augmentation for Commonsense Reasoning

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

The Right Tool for the Job: Matching Model and Instance Complexities

Adversarial Filters of Dataset Biases

Shallow Syntax in Deep Water

Syntactic Scaffolds for Semantic Structures

Polyglot Semantic Role Labeling

Learning Joint Semantic Parsers from Disjoint Data

Annotation Artifacts in Natural Language Inference Data

Multi-Mention Learning for Reading Comprehension with Neural Cascades

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

DyNet: The Dynamic Neural Network Toolkit

Greedy, Joint Syntactic-Semantic Parsing with Stack LSTMs