Nithya Kota

dblp:390/9275 · DBLP profile ↗
← Back
2ranked-venue papers in the field
0as first author
2since 2021 · last 2024
—ORCID · none

Domains — venue-derived; a paper can count in several

Big Data, Cloud & Distributed Data Systems · 2
YearPublicationVenuePosition
2024 Opportunities and Challenges of Generative-AI in Finance
abstract
Gen-AI techniques are able to improve understanding of context and nuances in language modeling, translation between languages, handle large volumes of data, provide fast, low-latency responses and can be fine-tuned for various tasks and domainsIn this manuscript, we present a comprehensive overview of the applications of Gen-AI techniques in the finance domain. In particular, we present the opportunities and challenges associated with the usage of Gen-AI techniques. We also illustrate the various methodologies which can be used to train Gen-AI techniques and present the various application areas of Gen-AI technologies in the finance ecosystemTo the best of our knowledge, this work represents the most comprehensive summarization of Gen-AI techniques within the financial domain. The analysis is designed for a deep overview of areas marked for substantial advancement while simultaneously pin-point those warranting future prioritization. We also hope that this work would serve as a conduit between finance and other domains, thus fostering the cross-pollination of innovative concepts and practices.
Akshar Prabhu Desai, Tejasvi Ravi, Mohammad Luqman, Ganesh Satish Mallya, Nithya Kota, Pranjul Yadav
IEEE Big Data5
2024 Gen-AI for User Safety: A Survey
abstract
In this manuscript, we provide a comprehensive overview of the various work done while using Gen-AI techniques w.r.t user safety. In particular, we first provide the various domains (e.g. phishing, malware, content moderation, counterfeit, physical safety) across which Gen-AI techniques have been applied. Next, we provide how Gen-AI techniques can be used in conjunction with various data modalities i.e. text, images, videos, audio, executable binaries to detect violations of user-safety. Further, also provide an overview of how Gen-AI techniques can be used in an adversarial setting. We believe that this work represents the first summarization of Gen-AI techniques for user-safety.
Akshar Prabhu Desai, Tejasvi Ravi, Mohammad Luqman, Nithya Kota, Pranjul Yadav
IEEE Big Data5