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Simultaneously evaluate $K$ policies in linear contextual bandits with near-optimal sample complexity by sharing information across evaluations via a unified ridge regression estimator.
A novel reward system boosts Qwen-Image-2.0's performance, achieving a 2.61 point increase in overall quality and significant gains in both text-to-image and image editing tasks.
Embedding geometric intelligence into segmentation models can dramatically enhance the recovery of small vascular structures and improve overall topology fidelity.
Language-driven video generation in Qwen-RobotWorld achieves unprecedented accuracy in predicting robotic actions, outperforming existing models across key benchmarks.
Rethinking few-step distillation reveals that the training pipeline's organization is as crucial as the distillation objectives themselves.
Existing text-to-image benchmarks miss the mark on real-world artistic creation, but Qwen-Image-Bench finally provides a creator-centric evaluation that reliably distinguishes state-of-the-art models.