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Real-time video object removal is now possible at 26 FPS, enabling interactive editing of arbitrarily long videos without latency or quality degradation.
Standard visual token pruning targets the wrong encoder depth: tapping into intermediate representations while asymmetrically skipping decoder sub-layers cuts MLLM inference FLOPs by 79% without requiring any retraining.
Agent memory can be compressed by 50% with virtually zero performance degradation (retaining up to 99.7% accuracy) and a 2x retrieval speedup by structuring historical context into event-centric maximum spanning trees.
AViTS reduces redundant computation in dynamic-resolution generation by up to 14.76x while preserving fine-detail consistency in outputs.
Achieving 5-7x speedup in diffusion models without sacrificing quality, LinCa redefines the efficiency of feature caching through adaptive prediction strategies.
Wuying-Browser-Agent achieves a groundbreaking 80.6% on WebVoyager, revealing that real-world browser agents can excel beyond short, clean demonstrations.
Output extrapolation in STEP-OPD enables a unified student model to surpass the performance of its specialized teachers across all evaluated tasks.