activity
20192022
most citedDiscovering Latent Concepts Learned in BERT

18 citations · 19 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20221 cited

SIT at MixMT 2022: Fluent Translation Built on Giant Pre-trained Models

Abdul Rafae Khan, Hrishikesh Kanade, Girish Amar Budhrani +2

This paper describes the Stevens Institute of Technology's submission for the WMT 2022 Shared Task: Code-mixed Machine Translation (MixMT). The task consisted of two subtasks, subt…

cs.CL2022

ConceptX: A Framework for Latent Concept Analysis

Firoj Alam, Fahim Dalvi, Nadir Durrani +3

The opacity of deep neural networks remains a challenge in deploying solutions where explanation is as important as precision. We present ConceptX, a human-in-the-loop framework fo…

cs.CL202218 cited

Discovering Latent Concepts Learned in BERT

Fahim Dalvi, Abdul Rafae Khan, Firoj Alam +3

A large number of studies that analyze deep neural network models and their ability to encode various linguistic and non-linguistic concepts provide an interpretation of the inner…

cs.LG2021

Interpreting Criminal Charge Prediction and Its Algorithmic Bias via Quantum-Inspired Complex Valued Networks

Abdul Rafae Khan, Jia Xu, Peter Varsanyi +1

While predictive policing has become increasingly common in assisting with decisions in the criminal justice system, the use of these results is still controversial. Some software…

cs.CL2019

Diversity by Phonetics and its Application in Neural Machine Translation

Abdul Rafae Khan, Jia Xu

We introduce a powerful approach for Neural Machine Translation (NMT), whereby, during training and testing, together with the input we provide its phonetic encoding and the varian…