3 papers
cs.CL2025
Insights from the Inverse: Reconstructing LLM Training Goals Through Inverse Reinforcement Learning
Jared Joselowitz, Ritam Majumdar, Arjun Jagota +4
Large language models (LLMs) trained with Reinforcement Learning from Human Feedback (RLHF) have demonstrated remarkable capabilities, but their underlying reward functions and dec…
cs.LG2025
Improving ARDS Diagnosis Through Context-Aware Concept Bottleneck Models
Anish Narain, Ritam Majumdar, Nikita Narayanan +2
Large, publicly available clinical datasets have emerged as a novel resource for understanding disease heterogeneity and to explore personalization of therapy. These datasets are d…
stat.ML2024
Concept-driven Off Policy Evaluation
Ritam Majumdar, Jack Teversham, Sonali Parbhoo
Evaluating off-policy decisions using batch data poses significant challenges due to limited sample sizes leading to high variance. To improve Off-Policy Evaluation (OPE), we must…