机器学习
47 篇 · 资讯流SomaAlign: Reliability-Aware Multimodal Representation Learning for Soft Robotic Grasping
Robust multimodal perception for soft robotic grasping is challenged by modality-dependent noise, semantic ambiguity, an
原文 ↗ElectroChemLLM: A Multimodal LLM Pipeline for High-Fidelity Electrochemical Informatics
Electrochemistry is central to solving many modern-day challenges, including energy storage systems for a sustainable fu
原文 ↗Gym-Anything for Robotics: Scaling physical simulations with digital agents
Realistic, fast robotics simulations could enable large-scale training of embodied AI models that transfer to the real w
原文 ↗TAPESTRY: A Single Backbone for Video Generation and Robot Control
Pretrained video generation models encode rich priors about physical interactions, but leveraging them for robot control
原文 ↗Multi-Objective Reinforcement Learning Using Routed Ensembles and Trajectory Attribution
Multi-objective reinforcement learning is a fundamental problem for modern AI, with applications spanning post-training,
原文 ↗Dream to Assist: Intent-Conditioned World Models for Shared Vehicle Control
Assistive agents in shared-control settings face a dual challenge: acting proactively to align with the human's intentio
原文 ↗Democratizing LLM Training with the Edge: Challenges, Systems, and the Road Ahead
The growing computational power of modern GPU data centers has let a few industrial giants train and deploy large langua
原文 ↗Sensorimotor Alignment: A Platonic Proxy for Embodied Policy Success
Robotic foundation models are typically evaluated through costly closed-loop rollouts, which motivates cheap offline pro
原文 ↗Learning Robot Behavior Priors from Non-Robotic Synthetic Data
Real robot data, rich across tasks and morphologies, is often treated as the bottleneck for training robot learning mode
原文 ↗Causal world models under physical parameter shifts
World models predict how embodied systems evolve under actions, but their accuracy can degrade when physical conditions
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