24 citations · 25 across the 8 of their papers we have counts for
4 papers · 2 filters
IntenDD: A Unified Contrastive Learning Approach for Intent Detection and Discovery
Bhavuk Singhal, Ashim Gupta, Shivasankaran V P +1
Identifying intents from dialogue utterances forms an integral component of task-oriented dialogue systems. Intent-related tasks are typically formulated either as a classification…
Adversarial Clean Label Backdoor Attacks and Defenses on Text Classification Systems
Ashim Gupta, Amrith Krishna
Clean-label (CL) attack is a form of data poisoning attack where an adversary modifies only the textual input of the training data, without requiring access to the labeling functio…
Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text
Ashim Gupta, Carter Wood Blum, Temma Choji +4
Can language models transform inputs to protect text classifiers against adversarial attacks? In this work, we present ATINTER, a model that intercepts and learns to rewrite advers…
Sāmayik: A Benchmark and Dataset for English-Sanskrit Translation
Ayush Maheshwari, Ashim Gupta, Amrith Krishna +4
We release Sāmayik, a dataset of around 53,000 parallel English-Sanskrit sentences, written in contemporary prose. Sanskrit is a classical language still in sustenance and has a ri…