3 citations · 3 across the 5 of their papers we have counts for
5 papers
Privacy-Preserving Federated Learning: Integrating Zero-Knowledge Proofs in Scalable Distributed Architectures
Divya Gupta
The intersection of Artificial Intelligence (AI) and distributed systems has given rise to Federated Learning (FL), a paradigm that enables decentralized model training without com…
Enterprise AI Must Enforce Participant-Aware Access Control
Shashank Shreedhar Bhatt, Tanmay Rajore, Khushboo Aggarwal +10
Large language models (LLMs) are increasingly deployed in enterprise settings where they interact with multiple users and are trained or fine-tuned on sensitive internal data. Whil…
TRUCE: Private Benchmarking to Prevent Contamination and Improve Comparative Evaluation of LLMs
Tanmay Rajore, Nishanth Chandran, Sunayana Sitaram +4
Benchmarking is the de-facto standard for evaluating LLMs, due to its speed, replicability and low cost. However, recent work has pointed out that the majority of the open source b…
TrustRate: A Decentralized Platform for Hijack-Resistant Anonymous Reviews
Rohit Dwivedula, Sriram Sridhar, Sambhav Satija +4
Reviews and ratings by users form a central component in several widely used products today (e.g., product reviews, ratings of online content, etc.), but today's platforms for mana…
Privacy Preserving Multi-Agent Reinforcement Learning in Supply Chains
Ananta Mukherjee, Peeyush Kumar, Boling Yang +2
This paper addresses privacy concerns in multi-agent reinforcement learning (MARL), specifically within the context of supply chains where individual strategic data must remain con…