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GigaWorld-Policy-0.5 achieves real-time robot control with 85 ms inference latency by decoupling visual dynamics from action generation, revolutionizing WAM efficiency.
Evaluator quality for robotic policies hinges more on long-horizon consistency than on short-term visual fidelity, reshaping our approach to world model design.
Spatial-semantic prompting outperforms traditional text-only methods in embodied visual tracking, especially in complex environments with similar distractors.
ATHENA accelerates influence computation for billion-parameter models, achieving a staggering 313.4x speedup while maintaining or improving task performance with significantly less data.
CoT fine-tuning can slash long-range recall by over 57% in hybrid LLMs, but a simple parameter restoration method can reverse this trend without additional training.
EM-Fall's embodied sensing approach enables humanoid robots to maintain effective fall detection even in challenging environments, outperforming traditional systems.
Robots can now understand and act on your gaze while following language commands, enabling more intuitive and precise human-robot collaboration.
