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Standard text-prompt evaluations severely underestimate diffusion safety risks, which reliably resurface under embedding-level control and trigger policy enforcement failures unless probabilities are explicitly calibrated.
Achieving a balance between pattern preservation and attribute retrieval, this method boosts retrieval performance while maintaining fine-grained contextual integrity.
InDex bridges the morphology gap, enabling VLA models to excel in dexterous manipulation with minimal data while preserving spatial reasoning.
MLT-Dedup slashes online video repetition rates by 91% while boosting indexing capacity fivefold, revolutionizing deduplication efficiency.
Reinforcement learning boosts multimodal performance, raising task scores and creating unexpected synergies between image generation and editing.
