activity
20172025
most citedConformer: Convolution-augmented Transformer for Speech Recognition

387 citations · 877 across the 7 of their papers we have counts for

collaborators
Showing cs.CLShow all

6 papers · 1 filter

cs.CL20241 cited

Synthetic Data Generation and Joint Learning for Robust Code-Mixed Translation

Kartik Kartik, Sanjana Soni, Anoop Kunchukuttan +2

The widespread online communication in a modern multilingual world has provided opportunities to blend more than one language (aka code-mixed language) in a single utterance. This…

cs.CL2024

A Dataset for Metaphor Detection in Early Medieval Hebrew Poetry

Michael Toker, Oren Mishali, Ophir Münz-Manor +2

There is a large volume of late antique and medieval Hebrew texts. They represent a crucial linguistic and cultural bridge between Biblical and modern Hebrew. Poetry is prominent i…

cs.CL2021

Simple and Efficient ways to Improve REALM

Vidhisha Balachandran, Ashish Vaswani, Yulia Tsvetkov +1

Dense retrieval has been shown to be effective for retrieving relevant documents for Open Domain QA, surpassing popular sparse retrieval methods like BM25. REALM (Guu et al., 2020)…

cs.CL2019

Corpora Generation for Grammatical Error Correction

Jared Lichtarge, Chris Alberti, Shankar Kumar +3

Grammatical Error Correction (GEC) has been recently modeled using the sequence-to-sequence framework. However, unlike sequence transduction problems such as machine translation, G…

cs.CL2018

Weakly Supervised Grammatical Error Correction using Iterative Decoding

Jared Lichtarge, Christopher Alberti, Shankar Kumar +2

We describe an approach to Grammatical Error Correction (GEC) that is effective at making use of models trained on large amounts of weakly supervised bitext. We train the Transform…

cs.CL2018

The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation

Mia Xu Chen, Orhan Firat, Ankur Bapna +9

The past year has witnessed rapid advances in sequence-to-sequence (seq2seq) modeling for Machine Translation (MT). The classic RNN-based approaches to MT were first out-performed…