37 citations · 42 across the 5 of their papers we have counts for
5 papers
Debiasing Gender Bias in Information Retrieval Models
Dhanasekar Sundararaman, Vivek Subramanian
Biases in culture, gender, ethnicity, etc. have existed for decades and have affected many areas of human social interaction. These biases have been shown to impact machine learnin…
Improving Downstream Task Performance by Treating Numbers as Entities
Dhanasekar Sundararaman, Vivek Subramanian, Guoyin Wang +2
Numbers are essential components of text, like any other word tokens, from which natural language processing (NLP) models are built and deployed. Though numbers are typically not a…
How do lexical semantics affect translation? An empirical study
Vivek Subramanian, Dhanasekar Sundararaman
Neural machine translation (NMT) systems aim to map text from one language into another. While there are a wide variety of applications of NMT, one of the most important is transla…
Graph Convolutional Networks Reveal Neural Connections Encoding Prosthetic Sensation
Vivek Subramanian, Joshua Khani
Extracting stimulus features from neuronal ensembles is of great interest to the development of neuroprosthetics that project sensory information directly to the brain via electric…
Syntax-Infused Transformer and BERT models for Machine Translation and Natural Language Understanding
Dhanasekar Sundararaman, Vivek Subramanian, Guoyin Wang +4
Attention-based models have shown significant improvement over traditional algorithms in several NLP tasks. The Transformer, for instance, is an illustrative example that generates…