activity
20192024
most citedAdversarial Text Rewriting for Text-aware Recommender Systems

2 citations · 6 across the 8 of their papers we have counts for

collaborators

11 papers

cs.LG20221 cited

Robustness of Fusion-based Multimodal Classifiers to Cross-Modal Content Dilutions

Gaurav Verma, Vishwa Vinay, Ryan A. Rossi +1

As multimodal learning finds applications in a wide variety of high-stakes societal tasks, investigating their robustness becomes important. Existing work has focused on understand…

cs.LG20221 cited

Overcoming Language Disparity in Online Content Classification with Multimodal Learning

Gaurav Verma, Rohit Mujumdar, Zijie J. Wang +2

Advances in Natural Language Processing (NLP) have revolutionized the way researchers and practitioners address crucial societal problems. Large language models are now the standar…

cs.CL2021

DRAG: Director-Generator Language Modelling Framework for Non-Parallel Author Stylized Rewriting

Hrituraj Singh, Gaurav Verma, Aparna Garimella +1

Author stylized rewriting is the task of rewriting an input text in a particular author's style. Recent works in this area have leveraged Transformer-based language models in a den…

cs.CL2020

Incorporating Stylistic Lexical Preferences in Generative Language Models

Hrituraj Singh, Gaurav Verma, Balaji Vasan Srinivasan

While recent advances in language modeling have resulted in powerful generation models, their generation style remains implicitly dependent on the training data and can not emulate…

cs.CL2020

LynyrdSkynyrd at WNUT-2020 Task 2: Semi-Supervised Learning for Identification of Informative COVID-19 English Tweets

Abhilasha Sancheti, Kushal Chawla, Gaurav Verma

We describe our system for WNUT-2020 shared task on the identification of informative COVID-19 English tweets. Our system is an ensemble of various machine learning methods, levera…

cs.CL20201 cited

"To Target or Not to Target": Identification and Analysis of Abusive Text Using Ensemble of Classifiers

Gaurav Verma, Niyati Chhaya, Vishwa Vinay

With rising concern around abusive and hateful behavior on social media platforms, we present an ensemble learning method to identify and analyze the linguistic properties of such…