Visual and action data are interconnected in robotic tasks, forming a perception-action loop. Robots rely on control parameters for movement, ...
Model fusion, particularly within the realm of large language models (LLM), presents an intriguing challenge that addresses the growing demand ...
In traffic management and urban planning, the ability to learn optimal routes from demonstrations conditioned on contextual features is very ...
Merge-of-experts (MoE) architectures use sparse activation to initialize scaling of model sizes while preserving high inference and training efficiency. However, ...
Distinguishing the fine boundaries of an image, especially in noisy or low-resolution settings, remains a formidable task. Traditional approaches, which ...
