activity
20182021
most citedAttention Interpretability Across NLP Tasks

69 citations · 72 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL20211 cited

Increasing Faithfulness in Knowledge-Grounded Dialogue with Controllable Features

Hannah Rashkin, David Reitter, Gaurav Singh Tomar +1

Knowledge-grounded dialogue systems are intended to convey information that is based on evidence provided in a given source text. We discuss the challenges of training a generative…

cs.CL2019

Thieves on Sesame Street! Model Extraction of BERT-based APIs

Kalpesh Krishna, Gaurav Singh Tomar, Ankur P. Parikh +2

We study the problem of model extraction in natural language processing, in which an adversary with only query access to a victim model attempts to reconstruct a local copy of that…

cs.CL20192 cited

Improving Semantic Parsing with Neural Generator-Reranker Architecture

Huseyin A. Inan, Gaurav Singh Tomar, Huapu Pan

Semantic parsing is the problem of deriving machine interpretable meaning representations from natural language utterances. Neural models with encoder-decoder architectures have re…

cs.CL201969 cited

Attention Interpretability Across NLP Tasks

Shikhar Vashishth, Shyam Upadhyay, Gaurav Singh Tomar +1

The attention layer in a neural network model provides insights into the model's reasoning behind its prediction, which are usually criticized for being opaque. Recently, seemingly…

cs.IR2018

End-to-End Retrieval in Continuous Space

Daniel Gillick, Alessandro Presta, Gaurav Singh Tomar

Most text-based information retrieval (IR) systems index objects by words or phrases. These discrete systems have been augmented by models that use embeddings to measure similarity…