1 code implementation • NeurIPS 2023 • Tung Nguyen, Jason Jewik, Hritik Bansal, Prakhar Sharma, Aditya Grover
Modeling weather and climate is an essential endeavor to understand the near- and long-term impacts of climate change, as well as inform technology and policymaking for adaptation and mitigation efforts.
1 code implementation • Findings (ACL) 2022 • Zichao Li, Prakhar Sharma, Xing Han Lu, Jackie C. K. Cheung, Siva Reddy
We train a neural model with this feedback data that can generate explanations and re-score answer candidates.
Ranked #1 on Overall - Test on FeedbackQA
1 code implementation • 27 Sep 2021 • Soumyadeep Roy, Sudip Chakraborty, Aishik Mandal, Gunjan Balde, Prakhar Sharma, Anandhavelu Natarajan, Megha Khosla, Shamik Sural, Niloy Ganguly
Online medical forums have become a predominant platform for answering health-related information needs of consumers.
no code implementations • 23 Apr 2021 • Prakhar Sharma, Phillip Porras, Steven Cheung, James Carpenter, Vinod Yegneswaran
We present a deep learning based approach to containerized application runtime stability analysis, and an intelligent publishing algorithm that can dynamically adjust the depth of process-level forensics published to a backend incident analysis repository.
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.
no code implementations • 25 Feb 2019 • Cagri Ozcaglar, Sahin Geyik, Brian Schmitz, Prakhar Sharma, Alex Shelkovnykov, Yiming Ma, Erik Buchanan
Talent Search systems aim to recommend potential candidates who are a good match to the hiring needs of a recruiter expressed in terms of the recruiter's search query or job posting.