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08/14/2023
The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation
Automatic evaluation of machine translation (MT) is a critical tool driv...
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06/12/2023
Benchmarking Neural Network Training Algorithms
Training algorithms, broadly construed, are an essential part of every d...
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02/09/2023
Binarized Neural Machine Translation
The rapid scaling of language models is motivating research using low-bi...
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09/23/2022
Do Current Multi-Task Optimization Methods in Deep Learning Even Help?
Recent research has proposed a series of specialized optimization algori...
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02/04/2022
Data Scaling Laws in NMT: The Effect of Noise and Architecture
In this work, we study the effect of varying the architecture and traini...
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10/08/2021
A Loss Curvature Perspective on Training Instability in Deep Learning
In this work, we study the evolution of the loss Hessian across many cla...
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10/06/2021
Efficient and Private Federated Learning with Partially Trainable Networks
Federated learning is used for decentralized training of machine learnin...
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02/18/2021
Echo State Speech Recognition
We propose automatic speech recognition (ASR) models inspired by echo st...
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10/28/2020
The geometry of integration in text classification RNNs
Despite the widespread application of recurrent neural networks (RNNs) a...
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02/27/2020
Echo State Neural Machine Translation
We present neural machine translation (NMT) models inspired by echo stat...
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12/28/2018
