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ROOT: Discovering Rewards for User-Specified Embodied Behaviors
Eren Sadikoglu, Aditya Taparia, Xinyuan Liu +1
Reinforcement learning for embodied control remains constrained by the difficulty of reward specification. Although recent large language model (LLM)-based methods can synthesize r…
PhysicsLENS: Diagnosing Physical Property Blindness in Video Generation Models
Isaiah Milkey, Som Sagar, Aditya Taparia +3
Reliable video world models could provide scalable predictive environments for robot learning, planning, and evaluation. However, generated robot videos can violate physical princi…
The Anatomy of Uncertainty in LLMs
Aditya Taparia, Ransalu Senanayake, Kowshik Thopalli +1
Understanding why a large language model (LLM) is uncertain about the response is important for their reliable deployment. Current approaches, which either provide a single uncerta…
Learning to Configure Agentic AI Systems
Aditya Taparia, Som Sagar, Ransalu Senanayake
Configuring LLM-based agent systems involves choosing workflows, tools, token budgets, and prompts from a large combinatorial design space, and is typically handled today by fixed…