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Shopping agents struggle to achieve even 60% accuracy in uncovering hidden shopper intents across complex tasks, revealing critical gaps in current AI capabilities.
Semantic-ID tokenizers, a promising approach for generative recommendation, can inflate Hit@K metrics by over 100% due to collisions where multiple items map to the same token sequence.
