no code implementations • DravidianLangTech (ACL) 2022 • Ramaneswaran S, Sanchit Vijay, Kathiravan Srinivasan
Task-Oriented Dialogue (TOD) systems allow users to accomplish tasks by giving directions to the system using natural language utterances.
1 code implementation • COLING (WNUT) 2022 • Ramaneswaran S, Sean Benhur, Sreyan Ghosh
Sentiment classification is a fundamental NLP task of detecting the sentiment polarity of a given text.
1 code implementation • 30 Mar 2024 • Chandra Kiran Reddy Evuru, Sreyan Ghosh, Sonal Kumar, Ramaneswaran S, Utkarsh Tyagi, Dinesh Manocha
We present CoDa (Constrained Generation based Data Augmentation), a controllable, effective, and training-free data augmentation technique for low-resource (data-scarce) NLP.
no code implementations • 3 Feb 2024 • Sreyan Ghosh, Chandra Kiran Reddy Evuru, Sonal Kumar, Ramaneswaran S, Deepali Aneja, Zeyu Jin, Ramani Duraiswami, Dinesh Manocha
Our findings reveal that responses generated solely from pre-trained knowledge consistently outperform responses by models that learn any form of new knowledge from IT on open-source datasets.
1 code implementation • 19 Oct 2023 • Shivani Kumar, Ramaneswaran S, Md Shad Akhtar, Tanmoy Chakraborty
Recognizing that emotional intelligence encompasses a comprehension of worldly knowledge, we propose an innovative approach that integrates commonsense information with dialogue context to facilitate a deeper understanding of emotions.
no code implementations • 25 Jul 2023 • Vikram Jamwal, Ramaneswaran S
This paper introduces Composite Diffusion as a means for artists to generate high-quality images by composing from the sub-scenes.
1 code implementation • 25 May 2023 • Shivam Sharma, Ramaneswaran S, Udit Arora, Md. Shad Akhtar, Tanmoy Chakraborty
In this work, we propose a novel task, MEMEX - given a meme and a related document, the aim is to mine the context that succinctly explains the background of the meme.