ICRA'25 Keynote
Harold gave a keynote at ICRA’25 on a foundation model for agents in embodied AI systems. Check it out below or on youtube: https://youtu.be/NCkwz0dBmO4?si=R...
Posts
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Diffusion Meets Options: Hierarchical Generative Skill Composition for Temporally-Extended Tasks
DOPPLER is a new framework that combines diffusion models and hierarchical reinforcement learning to let robots plan and replan complex, long-horizon tasks from offline data with robustness in the real world.
Know When to Abstain: Optimal Selective Classification with Likelihood Ratios
We propose optimal likelihood ratio-based selective classification methods based on the Neyman-Pearson lemma and evaluate them under vision and language covariate shifts tasks.
Introducing Dr. Kaiqi Chen!
Kaiqi Chen successfully defended his thesis and is now Dr. Chen. Congratulations Kaiqi!
KOAP: Imitation Learning with Limited Actions via Diffusion Planners and Deep Koopman Controllers
We introduce KOAP for imitation learning with limited actions.
SocRATES: Towards Automated Scenario-based Testing of Social Navigation Algorithms
We design an LLM-driven social-scenario simulation pipeline (SocRATES) to enable more holistic evaluation of social navigation algorithms. SocRATES generates context- and location-appropriate scenarios from simple text and image-based inputs, thus reducing the labor-intensive task of scenario proposal and synthesis that is typically required for scenario-based testing.
Out-of-Distribution Detection with a Single Unconditional Diffusion Model
We show that a single unconditional diffusion model performs competitively in out-of-distribution detection tasks by measuring the rate-of-change and curvature of diffusion paths connecting data samples to the standard normal distribution.