STRONG-VLA uses decoupled two-stage training to improve VLA model robustness, yielding up to 16% higher task success rates under seen and unseen perturbations on the LIBERO benchmark.
Eva-VLA: Evaluating vision-language-action mod- els’ robustness under real-world physical variations
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Thermally activated clothing with thermochromic dyes and heaters creates dynamic adversarial patterns that evade AI surveillance in visible and infrared modalities while appearing ordinary when inactive.
AFIL trains dual action generators on success and failure rollouts from a pretrained VLA to steer diffusion policies away from failure modes during inference.
citing papers explorer
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STRONG-VLA: Decoupled Robustness Learning for Vision-Language-Action Models under Multimodal Perturbations
STRONG-VLA uses decoupled two-stage training to improve VLA model robustness, yielding up to 16% higher task success rates under seen and unseen perturbations on the LIBERO benchmark.
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Thermally Activated Dual-Modal Adversarial Clothing against AI Surveillance Systems
Thermally activated clothing with thermochromic dyes and heaters creates dynamic adversarial patterns that evade AI surveillance in visible and infrared modalities while appearing ordinary when inactive.
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Failing Forward: Adaptive Failure-Informed Learning for Vision-Language-Action Models
AFIL trains dual action generators on success and failure rollouts from a pretrained VLA to steer diffusion policies away from failure modes during inference.
- Lost in Fog: Sensor Perturbations Expose Reasoning Fragility in Driving VLAs