1 citations · 2 across the 4 of their papers we have counts for
5 papers
Reward-Driven Learning under Prompt-Level Differential Privacy
Jiachen Zhao, Antonia Januszewicz, Taeho Jung
Reinforcement learning with verifiable rewards (RLVR) trains a language model on problems that may themselves be confidential, and the trained model can reveal which problems it sa…
Position: Privacy Is a Claim, Not a Property of Synthetic Data
Jiachen Zhao, Antonia Januszewicz, Taeho Jung
Synthetic data has become a common component of machine learning research. While widely adopted, its use in privacy-sensitive contexts has quietly shifted from a claim of residual…
A Technical Policy Blueprint for Trustworthy Decentralized AI
Hasan Kassem, Orion Banks, Omar Benjelloun +20
Decentralized AI systems, such as federated learning, can play a critical role in further unlocking AI asset marketplaces (e.g., healthcare data marketplaces) thanks to increased a…
A Decentralized Retrieval Augmented Generation System with Source Reliabilities Secured on Blockchain
Yining Lu, Wenyi Tang, Max Johnson +2
Existing retrieval-augmented generation (RAG) systems typically use a centralized architecture, causing a high cost of data collection, integration, and management, as well as priv…
Web3DB: Web 3.0 RDBMS for Individual Data Ownership
Shankha Shubhra Mukherjee, Wenyi Tang, Gustavo Prado Fenzi Aniceto +3
This paper introduces Web3DB, a decentralized relational database management system (RDBMS) designed to align with the principles of Web 3.0, addressing critical shortcomings of tr…