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12/19/2022
Less is More: Parameter-Free Text Classification with Gzip
Deep neural networks (DNNs) are often used for text classification tasks...
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11/21/2022
SpeechNet: Weakly Supervised, End-to-End Speech Recognition at Industrial Scale
End-to-end automatic speech recognition systems represent the state of t...
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10/10/2022
What the DAAM: Interpreting Stable Diffusion Using Cross Attention
Large-scale diffusion neural networks represent a substantial milestone ...
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07/31/2022
Building an Efficiency Pipeline: Commutativity and Cumulativeness of Efficiency Operators for Transformers
There exists a wide variety of efficiency methods for natural language p...
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12/27/2020
Inserting Information Bottlenecks for Attribution in Transformers
Pretrained transformers achieve the state of the art across tasks in nat...
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08/21/2020
Howl: A Deployed, Open-Source Wake Word Detection System
We describe Howl, an open-source wake word detection toolkit with native...
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07/14/2020
Covidex: Neural Ranking Models and Keyword Search Infrastructure for the COVID-19 Open Research Dataset
We present Covidex, a search engine that exploits the latest neural rank...
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04/28/2020
Showing Your Work Doesn't Always Work
In natural language processing, a recently popular line of work explores...
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04/27/2020
DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference
Large-scale pre-trained language models such as BERT have brought signif...
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04/23/2020
Rapidly Bootstrapping a Question Answering Dataset for COVID-19
We present CovidQA, the beginnings of a question answering dataset speci...
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11/08/2019
What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning
Pretrained transformer-based language models have achieved state of the ...
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11/07/2019
Explicit Pairwise Word Interaction Modeling Improves Pretrained Transformers for English Semantic Similarity Tasks
In English semantic similarity tasks, classic word embedding-based appro...
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04/17/2019
DocBERT: BERT for Document Classification
Pre-trained language representation models achieve remarkable state of t...
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03/28/2019
Distilling Task-Specific Knowledge from BERT into Simple Neural Networks
In the natural language processing literature, neural networks are becom...
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12/19/2018
Streaming Voice Query Recognition using Causal Convolutional Recurrent Neural Networks
Voice-enabled commercial products are ubiquitous, typically enabled by l...
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11/07/2018
FLOPs as a Direct Optimization Objective for Learning Sparse Neural Networks
There exists a plethora of techniques for inducing structured sparsity i...
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11/02/2018
Progress and Tradeoffs in Neural Language Models
In recent years, we have witnessed a dramatic shift towards techniques d...
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10/30/2018
JavaScript Convolutional Neural Networks for Keyword Spotting in the Browser: An Experimental Analysis
Used for simple commands recognition on devices from smart routers to mo...
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09/27/2018
Adaptive Pruning of Neural Language Models for Mobile Devices
Neural language models (NLMs) exist in an accuracy-efficiency tradeoff s...
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10/30/2017
An Experimental Analysis of the Power Consumption of Convolutional Neural Networks for Keyword Spotting
Nearly all previous work on small-footprint keyword spotting with neural...
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10/28/2017
Deep Residual Learning for Small-Footprint Keyword Spotting
We explore the application of deep residual learning and dilated convolu...
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10/18/2017