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05/24/2022
Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing
Despite their strong performance on many tasks, pre-trained language mod...
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10/12/2020
Measuring and Reducing Gendered Correlations in Pre-trained Models
Pre-trained models have revolutionized natural language understanding. H...
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06/16/2020
Scalable Cross Lingual Pivots to Model Pronoun Gender for Translation
Machine translation systems with inadequate document understanding can m...
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04/24/2020
Syntactic Data Augmentation Increases Robustness to Inference Heuristics
Pretrained neural models such as BERT, when fine-tuned to perform natura...
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04/24/2020
Collecting Entailment Data for Pretraining: New Protocols and Negative Results
Textual entailment (or NLI) data has proven useful as pretraining data f...
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08/31/2019
Giving BERT a Calculator: Finding Operations and Arguments with Reading Comprehension
Reading comprehension models have been successfully applied to extractiv...
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06/12/2019
Synthetic QA Corpora Generation with Roundtrip Consistency
We introduce a novel method of generating synthetic question answering c...
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05/21/2018
Morphosyntactic Tagging with a Meta-BiLSTM Model over Context Sensitive Token Encodings
The rise of neural networks, and particularly recurrent neural networks,...
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08/01/2017
