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06/13/2023
Large-scale Language Model Rescoring on Long-form Data
In this work, we study the impact of Large-scale Language Models (LLM) o...
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11/28/2022
E2E Segmentation in a Two-Pass Cascaded Encoder ASR Model
We explore unifying a neural segmenter with two-pass cascaded encoder AS...
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10/31/2022
Modular Hybrid Autoregressive Transducer
Text-only adaptation of a transducer model remains challenging for end-t...
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04/22/2022
E2E Segmenter: Joint Segmenting and Decoding for Long-Form ASR
Improving the performance of end-to-end ASR models on long utterances ra...
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04/20/2022
Detecting Unintended Memorization in Language-Model-Fused ASR
End-to-end (E2E) models are often being accompanied by language models (...
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03/09/2022
Sentence-Select: Large-Scale Language Model Data Selection for Rare-Word Speech Recognition
Language model fusion helps smart assistants recognize words which are r...
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04/30/2021
Scaling End-to-End Models for Large-Scale Multilingual ASR
Building ASR models across many language families is a challenging multi...
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04/09/2021
Lookup-Table Recurrent Language Models for Long Tail Speech Recognition
We introduce Lookup-Table Language Models (LookupLM), a method for scali...
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02/16/2021
GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training
Changes in neural architectures have fostered significant breakthroughs ...
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09/04/2020
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching
Data Poisoning attacks involve an attacker modifying training data to ma...
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04/01/2020
MetaPoison: Practical General-purpose Clean-label Data Poisoning
Data poisoning–the process by which an attacker takes control of a model...
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10/15/2019
DeepErase: Weakly Supervised Ink Artifact Removal in Document Text Images
Paper-intensive industries like insurance, law, and government have long...
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09/29/2019
Strong Baseline Defenses Against Clean-Label Poisoning Attacks
Targeted clean-label poisoning is a type of adversarial attack on machin...
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06/07/2019
Understanding Generalization through Visualizations
The power of neural networks lies in their ability to generalize to unse...
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05/15/2019
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets
In this paper, we explore clean-label poisoning attacks on deep convolut...
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04/15/2019
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent
The goal of this paper is to study why stochastic gradient descent (SGD)...
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11/27/2018
Accurate, Data-Efficient Learning from Noisy, Choice-Based Labels for Inherent Risk Scoring
Inherent risk scoring is an important function in anti-money laundering,...
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09/06/2018
Are adversarial examples inevitable?
A wide range of defenses have been proposed to harden neural networks ag...
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04/03/2018
