no code implementations • EMNLP 2020 • Nikhil Verma, Abhishek Sharma, Dhiraj Madan, Danish Contractor, Harshit Kumar, Sachindra Joshi
Neural Conversational QA tasks such as ShARC require systems to answer questions based on the contents of a given passage.
no code implementations • 3 Apr 2024 • Ali Pesaranghader, Nikhil Verma, Manasa Bharadwaj
In this paper, we propose GPT-DETOX as a framework for prompt-based in-context learning for text detoxification using GPT-3. 5 Turbo.
no code implementations • 11 Jul 2023 • Nikhil Verma, Deepkamal Kaur, Lydia Chau
The model proposed in this project is based on Vision Transformer (ViT) that takes 2D images as input and outputs embeddings which can be used for reconstructing denoised images.
no code implementations • 11 Jul 2023 • Nikhil Verma
With plethora of applications in diverse areas, generation of novel content using multiple modalities of data has remained a challenging problem.
no code implementations • 15 Dec 2021 • Nikhil Verma, Krishna Prasad
Recruiters can easily shortlist candidates for jobs via viewing their curriculum vitae (CV) document.
2 code implementations • 9 Sep 2019 • Nikhil Verma, Abhishek Sharma, Dhiraj Madan, Danish Contractor, Harshit Kumar, Sachindra Joshi
On studying recent state-of-the-art models on the ShARCQA task, we found indications that the models learn spurious clues/patterns in the dataset.
no code implementations • 20 Nov 2018 • Pravendra Singh, Vinay Sameer Raja Kadi, Nikhil Verma, Vinay P. Namboodiri
Convolutional neural networks (CNN) have achieved impressive performance on the wide variety of tasks (classification, detection, etc.)