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COVID-19 Deterioration Prediction via Self-Supervised Representation Learning and Multi-Image Prediction
The rapid spread of COVID-19 cases in recent months has strained hospita...
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Unnatural Language Inference
Natural Language Understanding has witnessed a watershed moment with the...
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A Closer Look at Codistillation for Distributed Training
Codistillation has been proposed as a mechanism to share knowledge among...
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Measuring Systematic Generalization in Neural Proof Generation with Transformers
We are interested in understanding how well Transformer language models ...
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Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop
This report documents ideas for improving the field of machine learning,...
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Probing Linguistic Systematicity
Recently, there has been much interest in the question of whether deep n...
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Learning an Unreferenced Metric for Online Dialogue Evaluation
Evaluating the quality of a dialogue interaction between two agents is a...
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Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program)
One of the challenges in machine learning research is to ensure that pre...
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Evaluating Logical Generalization in Graph Neural Networks
Recent research has highlighted the role of relational inductive biases ...
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CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text
The recent success of natural language understanding (NLU) systems has b...
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Compositional Language Understanding with Text-based Relational Reasoning
Neural networks for natural language reasoning have largely focused on e...
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The RLLChatbot: a solution to the ConvAI Challenge
Current conversational systems can follow simple commands and answer bas...
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Adversarial Gain
Adversarial examples can be defined as inputs to a model which induce a ...
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Ethical Challenges in Data-Driven Dialogue Systems
The use of dialogue systems as a medium for human-machine interaction is...
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