2 citations · 3 across the 3 of their papers we have counts for
3 papers
Reward Hacking Mitigation using Verifiable Composite Rewards
Mirza Farhan Bin Tarek, Rahmatollah Beheshti
Reinforcement Learning from Verifiable Rewards (RLVR) has recently shown that large language models (LLMs) can develop their own reasoning without direct supervision. However, appl…
Fairness-Optimized Synthetic EHR Generation for Arbitrary Downstream Predictive Tasks
Mirza Farhan Bin Tarek, Raphael Poulain, Rahmatollah Beheshti
Among various aspects of ensuring the responsible design of AI tools for healthcare applications, addressing fairness concerns has been a key focus area. Specifically, given the wi…
Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods
Raphael Poulain, Mirza Farhan Bin Tarek, Rahmatollah Beheshti
Developing AI tools that preserve fairness is of critical importance, specifically in high-stakes applications such as those in healthcare. However, health AI models' overall predi…