CLeAR wins REAL-I 2026 Embodied AI Challenge!
CLeAR took Overall Champion at REAL-I 2026, the 1st Real-World Embodied AI Learning Challenge, held at ICRA 2026.
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TOPO-Bench: Benchmarking Topological Mapping under Perceptual Aliasing
An open-source framework for evaluating topological mapping, with the first quantitative measure of dataset ambiguity (perceptual aliasing).
On-Manifold Guidance @ ICML'26
We are excited to share that a paper from CLeAR has been accepted to ICML 2026! Here’s a snapshot: Conflict-Aware Additive Guidance for Flow Models under Co...
Steering & Skill Reuse @ R:SS'26
We are excited to share that two papers from CLeAR were accepted to R:SS 2026! More information about the papers is coming soon, but here’s a snapshot: ...
Introducing Dr. Ce Hao!
Ce Hao has graduated and is now Dr. Hao. Congratulations Ce! Ce’s PhD thesis, Advanced Diffusion Robot Manipulation Policies for Language Reasoning, Long-Ho...
Action Hallucination in Generative Vision-Language-Action Models
A theoretical analysis of why generative VLAs produce physically infeasible actions, identifying topological, precision, and horizon barriers that impose unavoidable tradeoffs.
Abstracting Robot Manipulation Skills via Mixture-of-Experts Diffusion Policies
Skill Mixture-of-Experts Policy (SMP)—a diffusion mixture-of-experts policy that learns a compact orthogonal skill basis and uses sticky routing for scalable, efficient multi-task manipulation.
