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Strong 3D perception and competitive motion planning in autonomous driving are achieved without sacrificing general vision-language understanding.
Token-level contrastive signals can streamline reasoning processes, leading to more efficient AI models without sacrificing performance.
Rationale-guided knowledge distillation boosts stance detection accuracy in low-resource languages by effectively transferring reasoning knowledge from powerful models to compact student models.
SAYRE's innovative approach to synthesizing KIE training data leads to substantial performance gains for on-device models, particularly in challenging extraction scenarios.
Despite impressive OCR performance on existing benchmarks, today's best LMMs still struggle with the messy realities of enterprise document processing.
