no code implementations • 25 Mar 2024 • Deepak Narayan Gadde, Aman Kumar, Thomas Nalapat, Evgenii Rezunov, Fabio Cappellini
This dataset was generated by 4 different LLMs and features a unique set of designs for each of the 10 CWEs we target in our paper.
no code implementations • 13 Mar 2024 • Aman Kumar, Khushboo Anand, Shubham Mandloi, Ashutosh Mishra, Avinash Thakur, Neeraj Kasera, Prathosh A P
Additionally, our approach also outperforms the state-of-the-art methods in achieving better inference time on various smart-phone chipsets and data-types making it a feasible solution for deployment on edge devices.
no code implementations • 13 Mar 2024 • M Rakesh Reddy, Shubham Mandloi, Aman Kumar
Moire pattern frequently appears in photographs captured with mobile devices and digital cameras, potentially degrading image quality.
no code implementations • 5 May 2023 • Xian Yeow Lee, Aman Kumar, Lasitha Vidyaratne, Aniruddha Rajendra Rao, Ahmed Farahat, Chetan Gupta
This paper focuses on solving a fault detection problem using multivariate time series of vibration signals collected from planetary gearboxes in a test rig.
no code implementations • NAACL (SUKI) 2022 • Aman Kumar, Akshay G Bharadwaj, Binil Starly, Collin Lynch
As the demands for large-scale information processing have grown, knowledge graph-based approaches have gained prominence for representing general and domain knowledge.
no code implementations • 10 Mar 2022 • Aman Kumar, Himani Shrotriya, Prachi Sahu, Raj Dabre, Ratish Puduppully, Anoop Kunchukuttan, Amogh Mishra, Mitesh M. Khapra, Pratyush Kumar
Natural Language Generation (NLG) for non-English languages is hampered by the scarcity of datasets in these languages.
no code implementations • 20 Nov 2021 • Aman Kumar, Swathi Dinakaran
A knowledge graph is an essential and trending technology with great applications in entity recognition, search, or question answering.
no code implementations • COLING 2016 • Aman Kumar, Hassan Alam, Tina Werner, Manan Vyas
In this study we develop a system that tags and extracts financial concepts called financial named entities (FNE) along with corresponding numeric values {--} monetary and temporal.