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Speaker recognition accuracy improves dramatically when leveraging a U-Net-based fusion of noisy and enhanced speech, coupled with a novel training strategy.
LLMs can now scale depth more effectively: a new attention mechanism recovers diluted features in deeper layers, boosting performance with negligible overhead.
Achieve state-of-the-art video generation with 24% fewer tokens by adaptively allocating tokens based on video segment complexity.
