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Concordia University
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CCBR empowers users to shape their recommendations through text-driven interactions, outperforming traditional models while maintaining high interpretability.
MambAdapter achieves superior performance in audio and speech tasks while drastically cutting down on computational resources.
Ditch the text: WavSLM shows you can train a competitive speech language model using only distilled WavLM representations, unlocking a simpler, single-stream generative pretraining paradigm for speech.
