5 papers
Comment on "Modeling rapid language learning by distilling Bayesian priors into artificial neural networks"
Orr Well, Idan Tarshish, Nur Lan +1
McCoy & Griffiths (2025, henceforth M&G) suggest that a Bayesian prior can be distilled into Artificial Neural Networks (ANNs) through Model-Agnostic Meta-Learning (MAML, Finn et a…
VGGT-SLAM++
Avilasha Mandal, Rajesh Kumar, Sudarshan Sunil Harithas +1
We introduce VGGT-SLAM++, a complete visual SLAM system that leverages the geometry-rich outputs of the Visual Geometry Grounded Transformer (VGGT). The system comprises a visual o…
DreamControl-v2: Simpler and Scalable Autonomous Humanoid Skills via Trainable Guided Diffusion Priors
Sudarshan Harithas, Sangkyung Kwak, Pushkal Katara +6
Developing robust autonomous loco-manipulation skills for humanoids remains an open problem in robotics. While RL has been applied successfully to legged locomotion, applying it to…
DreamControl: Human-Inspired Whole-Body Humanoid Control for Scene Interaction via Guided Diffusion
Dvij Kalaria, Sudarshan S Harithas, Pushkal Katara +7
We introduce DreamControl, a novel methodology for learning autonomous whole-body humanoid skills. DreamControl leverages the strengths of diffusion models and Reinforcement Learni…
MotionGlot: A Multi-Embodied Motion Generation Model
Sudarshan Harithas, Srinath Sridhar
This paper introduces MotionGlot, a model that can generate motion across multiple embodiments with different action dimensions, such as quadruped robots and human bodies. By lever…