138 citations · 179 across the 38 of their papers we have counts for
11 papers · 1 filter
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…
Dynamic Harness Search: Building Multi-Agent Systems Per-Query via Prediction
Som Sagar, Shasha Li, Hejie Cui +2
Agent harnesses specify the roles, instructions, tools, and communication structure used to solve a task, and the right harness depends on the query. Because the value of each desi…
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…
Test-Time Adaptation of Manipulation Policies Under Actuator Degradation
Som Sagar, Ransalu Senanayake
Robot manipulation policies are usually trained under the assumption that a commanded action produces the same motion as it did during training even after hours of operation. Real…
Physical Agentic AI: An Architecture for Orchestrating a Robot Crew with LLMs
Xinyuan Liu, Eren Sadikoglu, Riana Chatterjee +1
Agentic AI frameworks interpret open-ended task goals and decompose them into multi-step plans. Richer information about embodiment-specific capabilities, physical preconditions, a…
CUPID in the Model Zoo: Online Matchmaking for Selecting Your Dream LLM
Son Nguyen, Xinyuan Liu, Ransalu Senanayake
Users increasingly face the challenge of selecting an appropriate LLM for a given task from a rapidly growing pool of LLMs, each with distinct but often opaque latent properties. C…
MEMOR-E: In-Context and Fine-Tuned LLM Personalization for Alzheimer's Assistive Robotics
Maissa Abir Smaili, Eren Sadikoglu, Ransalu Senanayake
Alzheimer's disease is a neurodegenerative disorder marked by progressive declines in memory and language that reduce independence in daily life, motivating socially assistive robo…
LLM Routing as Reasoning: A MaxSAT View
Son Nguyen, Xinyuan Liu, Ransalu Senanayake
Routing a query through an appropriate LLM is challenging, particularly when user preferences are expressed in natural language and model attributes are only partially observable.…
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…
Humanoid Factors: Design Principles for AI Humanoids in Human Worlds
Xinyuan Liu, Eren Sadikoglu, Ransalu Senanayake +1
Human factors research has long focused on optimizing environments, tools, and systems to account for human performance. Yet, as humanoid robots begin to share our workplaces, home…