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05/24/2022
When More Data Hurts: A Troubling Quirk in Developing Broad-Coverage Natural Language Understanding Systems
In natural language understanding (NLU) production systems, users' evolv...
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06/08/2021
Coarse-to-Fine Curriculum Learning
When faced with learning challenging new tasks, humans often follow sequ...
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04/18/2021
Constrained Language Models Yield Few-Shot Semantic Parsers
We explore the use of large pretrained language models as few-shot seman...
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04/16/2021
Re-TACRED: Addressing Shortcomings of the TACRED Dataset
TACRED is one of the largest and most widely used sentence-level relatio...
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03/17/2021
HyperDynamics: Meta-Learning Object and Agent Dynamics with Hypernetworks
We propose HyperDynamics, a dynamics meta-learning framework that condit...
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12/09/2020
Improving Relation Extraction by Leveraging Knowledge Graph Link Prediction
Relation extraction (RE) aims to predict a relation between a subject an...
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04/07/2020
Learning from Imperfect Annotations
Many machine learning systems today are trained on large amounts of huma...
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02/15/2020
Jelly Bean World: A Testbed for Never-Ending Learning
Machine learning has shown growing success in recent years. However, cur...
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03/23/2019
Competence-based Curriculum Learning for Neural Machine Translation
Current state-of-the-art NMT systems use large neural networks that are ...
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08/26/2018
Contextual Parameter Generation for Universal Neural Machine Translation
We propose a simple modification to existing neural machine translation ...
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06/04/2018
Agreement-based Learning
Model selection is a problem that has occupied machine learning research...
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06/04/2018
Deep Graphs
We propose an algorithm for deep learning on networks and graphs. It rel...
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09/26/2017
