AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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In this technical report, we propose Pelican-Sim 1.0, a general world model simulator for embodied intelligence that predicts future observations from visual context and robot actions to support downstream learning and decision making. The model incorporates four key design features: (1) Unified action representation:...
Reward models are a bottleneck for reinforcement learning in embodied AI. Long-horizon robotic manipulation requires scalable vision feedback beyond handcrafted rewards or task-specific annotations. Existing open-source VLM reward judges like RoboReward adopt simple 1--5 trajectory progress scoring, lacking pairwise pr...
VLA-Trace is presented, a progressive diagnostic framework that analyzes VLA models through a unified evidence chain from representation dynamics to causal control attribution and behavioral manifestation to highlight future directions for representation-preserving adaptation, causal VLA circuits, and compositional sem...
A unified generative framework that leverages pre-trained Diffusion Transformer priors to achieve high perceptual quality at extremely low bitrates, achieving state-of-the-art perceptual fidelity with rich spatial details and robust temporal consistency.
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