most citedLeveraging Transformers for Hate Speech Detection in Conversational Code-Mixed Tweets

13 citations · 18 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2023

DALE: Generative Data Augmentation for Low-Resource Legal NLP

Sreyan Ghosh, Chandra Kiran Evuru, Sonal Kumar +4

We present DALE, a novel and effective generative Data Augmentation framework for low-resource LEgal NLP. DALE addresses the challenges existing frameworks pose in generating effec…

cs.CV2023

AdVerb: Visually Guided Audio Dereverberation

Sanjoy Chowdhury, Sreyan Ghosh, Subhrajyoti Dasgupta +3

We present AdVerb, a novel audio-visual dereverberation framework that uses visual cues in addition to the reverberant sound to estimate clean audio. Although audio-only dereverber…

cs.CL20233 cited

ACLM: A Selective-Denoising based Generative Data Augmentation Approach for Low-Resource Complex NER

Sreyan Ghosh, Utkarsh Tyagi, Manan Suri +3

Complex Named Entity Recognition (NER) is the task of detecting linguistically complex named entities in low-context text. In this paper, we present ACLM Attention-map aware keywor…

cs.CL20232 cited

BioAug: Conditional Generation based Data Augmentation for Low-Resource Biomedical NER

Sreyan Ghosh, Utkarsh Tyagi, Sonal Kumar +1

Biomedical Named Entity Recognition (BioNER) is the fundamental task of identifying named entities from biomedical text. However, BioNER suffers from severe data scarcity and lacks…

eess.AS2023

UNFUSED: UNsupervised Finetuning Using SElf supervised Distillation

Ashish Seth, Sreyan Ghosh, S. Umesh +1

In this paper, we introduce UnFuSeD, a novel approach to leverage self-supervised learning and reduce the need for large amounts of labeled data for audio classification. Unlike pr…

cs.CL202113 cited

Leveraging Transformers for Hate Speech Detection in Conversational Code-Mixed Tweets

Zaki Mustafa Farooqi, Sreyan Ghosh, Rajiv Ratn Shah

In the current era of the internet, where social media platforms are easily accessible for everyone, people often have to deal with threats, identity attacks, hate, and bullying du…