Raphael Tang | DeepAI

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Yue Zhang
236 publications
Kyunghyun Cho
218 publications
Jimmy Lin
120 publications
Yao Lu
73 publications
Lili Mou
59 publications
Rodrigo Nogueira
52 publications
Xiao Han
39 publications
Yaoliang Yu
37 publications
Xinyu Liu
25 publications
Zhiying Jiang
20 publications
Olga Vechtomova
18 publications

∙ 12/19/2022

Less is More: Parameter-Free Text Classification with Gzip

Deep neural networks (DNNs) are often used for text classification tasks...

0 Zhiying Jiang, et al. ∙

∙ 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...

0 Raphael Tang, et al. ∙

∙ 10/10/2022

What the DAAM: Interpreting Stable Diffusion Using Cross Attention

Large-scale diffusion neural networks represent a substantial milestone ...

1 Raphael Tang, et al. ∙

∙ 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...

0 Ji Xin, et al. ∙

∙ 12/27/2020

Inserting Information Bottlenecks for Attribution in Transformers

Pretrained transformers achieve the state of the art across tasks in nat...

0 Zhiying Jiang, et al. ∙

∙ 08/21/2020

Howl: A Deployed, Open-Source Wake Word Detection System

We describe Howl, an open-source wake word detection toolkit with native...

0 Raphael Tang, et al. ∙

∙ 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...

0 Edwin Zhang, et al. ∙

∙ 04/28/2020

Showing Your Work Doesn't Always Work

In natural language processing, a recently popular line of work explores...

0 Raphael Tang, et al. ∙

∙ 04/27/2020

DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference

Large-scale pre-trained language models such as BERT have brought signif...

0 Ji Xin, et al. ∙

∙ 04/23/2020

Rapidly Bootstrapping a Question Answering Dataset for COVID-19

We present CovidQA, the beginnings of a question answering dataset speci...

7 Raphael Tang, et al. ∙

∙ 11/08/2019

What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning

Pretrained transformer-based language models have achieved state of the ...

0 Jaejun Lee, et al. ∙

∙ 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...

0 Yinan Zhang, et al. ∙

∙ 04/17/2019

DocBERT: BERT for Document Classification

Pre-trained language representation models achieve remarkable state of t...

0 Ashutosh Adhikari, et al. ∙

∙ 03/28/2019

Distilling Task-Specific Knowledge from BERT into Simple Neural Networks

In the natural language processing literature, neural networks are becom...

0 Raphael Tang, et al. ∙

∙ 12/19/2018

Streaming Voice Query Recognition using Causal Convolutional Recurrent Neural Networks

Voice-enabled commercial products are ubiquitous, typically enabled by l...

0 Raphael Tang, et al. ∙

∙ 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...

0 Raphael Tang, et al. ∙

∙ 11/02/2018

Progress and Tradeoffs in Neural Language Models

In recent years, we have witnessed a dramatic shift towards techniques d...

0 Raphael Tang, et al. ∙

∙ 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...

0 Jaejun Lee, et al. ∙

∙ 09/27/2018

Adaptive Pruning of Neural Language Models for Mobile Devices

Neural language models (NLMs) exist in an accuracy-efficiency tradeoff s...

0 Raphael Tang, et al. ∙

∙ 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...

0 Raphael Tang, et al. ∙

∙ 10/28/2017

Deep Residual Learning for Small-Footprint Keyword Spotting

We explore the application of deep residual learning and dilated convolu...

0 Raphael Tang, et al. ∙

∙ 10/18/2017

Honk: A PyTorch Reimplementation of Convolutional Neural Networks for Keyword Spotting

We describe Honk, an open-source PyTorch reimplementation of convolution...

0 Raphael Tang, et al. ∙

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