iLearn-Lab

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   QuantWM targets flicker in 2-bit video-world-model caches

   Researchers from iLearn-Lab at Harbin Institute of Technology (Shenzhen) and LV-Lab at the National University of Singapore propose QuantWM, a training-free framework for 2-bit KV Cache quantization in video world models. The team says its query-sensitive clustering and low-rank attention compensation improve visual stability while achieving up to 6.20x KV Cache compression across five evaluated models.

   机器之心 · 🔥 6

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