no code implementations • 27 Dec 2023 • Karan Gupta, Sumegh Roychowdhury, Siva Rajesh Kasa, Santhosh Kumar Kasa, Anish Bhanushali, Nikhil Pattisapu, Prasanna Srinivasa Murthy
In the In-Context Learning (ICL) setup, various forms of label biases can manifest.
no code implementations • 6 Nov 2023 • Sumegh Roychowdhury, Karan Gupta, Siva Rajesh Kasa, Prasanna Srinivasa Murthy, Alok Chandra
Pre-trained language models (PLMs) have seen tremendous success in text classification (TC) problems in the context of Natural Language Processing (NLP).
1 code implementation • Findings (NAACL) 2022 • Souvic Chakraborty, Parag Dutta, Sumegh Roychowdhury, Animesh Mukherjee
The last decade has witnessed a surge in the interaction of people through social networking platforms.
no code implementations • NAACL 2022 • Bishal Santra, Sumegh Roychowdhury, Aishik Mandal, Vasu Gurram, Atharva Naik, Manish Gupta, Pawan Goyal
Although many pretrained models exist for text or images, there have been relatively fewer attempts to train representations specifically for dialog understanding.
no code implementations • 8 Sep 2021 • Sumedh A Sontakke, Sumegh Roychowdhury, Mausoom Sarkar, Nikaash Puri, Balaji Krishnamurthy, Laurent Itti
Humans excel at learning long-horizon tasks from demonstrations augmented with textual commentary, as evidenced by the burgeoning popularity of tutorial videos online.
no code implementations • 5 Nov 2020 • Ethan K. Gordon, Sumegh Roychowdhury, Tapomayukh Bhattacharjee, Kevin Jamieson, Siddhartha S. Srinivasa
Our key insight is that we can leverage the haptic context we collect during and after manipulation (i. e., "post hoc") to learn some of these properties and more quickly adapt our visual model to previously unseen food.
1 code implementation • 6 Oct 2020 • Sumegh Roychowdhury, Sumedh A. Sontakke, Nikaash Puri, Mausoom Sarkar, Milan Aggarwal, Pinkesh Badjatiya, Balaji Krishnamurthy, Laurent Itti
Also, they are believed to be arranged hierarchically, allowing for an efficient representation of complex long-horizon experiences.
no code implementations • 12 Apr 2020 • Bishal Santra, Prakhar Sharma, Sumegh Roychowdhury, Pawan Goyal
In this paper, we have explored the effects of different minibatch sampling techniques in Knowledge Graph Completion.
no code implementations • WS 2019 • Prakhar Sharma, Sumegh Roychowdhury
In this paper, we describe our system for COIN 2019 Shared Task 1: Commonsense Inference in Everyday Narrations.
no code implementations • WS 2019 • Prakhar Sharma, Sumegh Roychowdhury
Official System Description paper of Team IIT-KGP ranked 1st in the Development phase and 3rd in Testing Phase in MEDIQA 2019 - Recognizing Question Entailment (RQE) Shared Task of BioNLP workshop - ACL 2019.