no code implementations • EACL (HumEval) 2021 • Shaily Bhatt, Rahul Jain, Sandipan Dandapat, Sunayana Sitaram
We conduct experiments for evaluating an offensive content detection system and use a data augmentation technique for improving the model using insights from Checklist.
no code implementations • 21 Nov 2022 • Shaily Bhatt, Sunipa Dev, Partha Talukdar, Shachi Dave, Vinodkumar Prabhakaran
Recent research has revealed undesirable biases in NLP data and models.
1 code implementation • 25 Sep 2022 • Shaily Bhatt, Sunipa Dev, Partha Talukdar, Shachi Dave, Vinodkumar Prabhakaran
In this paper, we focus on NLP fair-ness in the context of India.
no code implementations • 24 Mar 2022 • Karthikeyan K, Shaily Bhatt, Pankaj Singh, Somak Aditya, Sandipan Dandapat, Sunayana Sitaram, Monojit Choudhury
We compare the TEA CheckLists with CheckLists created with different levels of human intervention.
no code implementations • 27 Sep 2021 • Shaily Bhatt, Sakshi Kalra, Naman Goenka, Yashvardhan Sharma
Easier access to the internet and social media has made disseminating information through online sources very easy.
no code implementations • ICON 2021 • Shaily Bhatt, Poonam Goyal, Sandipan Dandapat, Monojit Choudhury, Sunayana Sitaram
Deep Contextual Language Models (LMs) like ELMO, BERT, and their successors dominate the landscape of Natural Language Processing due to their ability to scale across multiple tasks rapidly by pre-training a single model, followed by task-specific fine-tuning.