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Bridging the gap between verbal and non-verbal vocalizations, this approach slashes speaker verification errors by over 40% while preserving speech accuracy.
Forget retraining LLMs from scratch for new architectures: PromptEmbedder lets you adapt to new backbones by only retraining a lightweight linear alignment matrix, slashing memory by 40% and speeding up training by 3.7x.
Forget retraining your retrieval model every time you add new documents – ICICLE lets you plug them in at inference time.
