21 citations · 22 across the 19 of their papers we have counts for
4 papers · 1 filter
Algorithmic Guarantees for Distilling Supervised and Offline RL Datasets
Aaryan Gupta, Rishi Saket, Aravindan Raghuveer
Given a training dataset, the goal of dataset distillation is to derive a synthetic dataset such that models trained on the latter perform as well as those trained on the training…
Dense and Diverse Goal Coverage in Multi Goal Reinforcement Learning
Sagalpreet Singh, Rishi Saket, Aravindan Raghuveer
Reinforcement Learning algorithms are primarily focused on learning a policy that maximizes expected return. As a result, the learned policy can exploit one or few reward sources.…
A Personalized Exercise Assistant using Reinforcement Learning (PEARL): Results from a four-arm Randomized-controlled Trial
Amy Armento Lee, Narayan Hegde, Nina Deliu +16
Consistent physical inactivity poses a major global health challenge. Mobile health (mHealth) interventions, particularly Just-in-Time Adaptive Interventions (JITAIs), offer a prom…
Robust Reward Modeling via Causal Rubrics
Pragya Srivastava, Harman Singh, Rahul Madhavan +9
Reward models (RMs) are fundamental to aligning Large Language Models (LLMs) via human feedback, yet they often suffer from reward hacking. They tend to latch on to superficial or…