101 citations · 161 across the 22 of their papers we have counts for
4 papers · 1 filter
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…
Toward Revealing Nuanced Biases in Medical LLMs
Farzana Islam Adiba, Rahmatollah Beheshti
Large language models (LLMs) used in medical applications are known to be prone to exhibiting biased and unfair patterns. Prior to deploying these in clinical decision-making, it i…
ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs
Fahmida Liza Piya, Rahmatollah Beheshti
Unstructured clinical data can serve as a unique and rich source of information that can meaningfully inform clinical practice. Extracting the most pertinent context from such data…
Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium
Amin Adibi, Xu Cao, Zongliang Ji +39
The fourth Machine Learning for Health (ML4H) symposium was held in person on December 15th and 16th, 2024, in the traditional, ancestral, and unceded territories of the Musqueam,…