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Training stability in Transformers can be achieved by constraining residual connections to orthogonal transformations, preventing the loss of diversity across layers.
Keyframe-residual captioning unlocks high-fidelity video-language supervision, surpassing direct VLM captioning in capturing fine-grained visual details.
A 1.7B parameter model can now rival much larger audio language models, thanks to a novel architecture and data synthesis pipeline.
