activity
20172020
most citedDistilling Task-Specific Knowledge from BERT into Simple Neural Networks

335 citations · 501 across the 10 of their papers we have counts for

collaborators

13 papers

cs.CL20202 cited

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

Raphael Tang, Jaejun Lee, Afsaneh Razi +4

We describe Howl, an open-source wake word detection toolkit with native support for open speech datasets, like Mozilla Common Voice and Google Speech Commands. We report benchmark…

cs.IR20207 cited

Covidex: Neural Ranking Models and Keyword Search Infrastructure for the COVID-19 Open Research Dataset

Edwin Zhang, Nikhil Gupta, Raphael Tang +8

We present Covidex, a search engine that exploits the latest neural ranking models to provide information access to the COVID-19 Open Research Dataset curated by the Allen Institut…

cs.CL20201 cited

Showing Your Work Doesn't Always Work

Raphael Tang, Jaejun Lee, Ji Xin +3

In natural language processing, a recently popular line of work explores how to best report the experimental results of neural networks. One exemplar publication, titled "Show Your…

cs.CL202019 cited

DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference

Ji Xin, Raphael Tang, Jaejun Lee +2

Large-scale pre-trained language models such as BERT have brought significant improvements to NLP applications. However, they are also notorious for being slow in inference, which…

cs.CL202062 cited

Rapidly Bootstrapping a Question Answering Dataset for COVID-19

Raphael Tang, Rodrigo Nogueira, Edwin Zhang +4

We present CovidQA, the beginnings of a question answering dataset specifically designed for COVID-19, built by hand from knowledge gathered from Kaggle's COVID-19 Open Research Da…

cs.CL201934 cited

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

Jaejun Lee, Raphael Tang, Jimmy Lin

Pretrained transformer-based language models have achieved state of the art across countless tasks in natural language processing. These models are highly expressive, comprising at…