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This work proposes HyGAE, an actor-critic framework that jointly optimizes token- and turn-level objectives with the hybrid advantage and unified critic and provides an in-depth analysis showing that the exact analytic form of the hybrid advantage and return is crucial for optimization.
ContextFlow is introduced, a conditional flow-matching model that learns continuous action distributions for in-context imitation learning and adapts perceiver-style multimodal context compressors that distill visual, proprioceptive, and action sequences into compact, task-relevant latent representations.
Pailitao-MMSearch is presented, one native e-commerce multimodal search foundation model designed to bridge this gap, and introduces three key innovations:HybSID (Hybrid Semantic ID);(2)a two-stage continual pre-training strategy; and (3)a hybrid reasoning post-training pipeline.
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