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arXiv AI By Xiaohan Ye, Zihan Gong, Jingqian Zhao, Lianyu Du, Yunmeng Shu, Xu Chen, Zesheng Zhou, Renchun You, Bocheng Chen, Jinsong Lan, Haihong Tang, Bo Zheng

PailitaoMMSearch2.0 Technical Report: Scaling Generative Retrieval to Unified End-to-End Multimodal Search

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The paper introduces PailitaoMMSearch2.0, a unified end‑to‑end multimodal search system that generates product Semantic IDs directly from an image and free‑form instruction. It scales across data, intent, and scenario dimensions using reusable data pipelines, continual pre‑training, mixed‑budget fine‑tuning, and reinforcement learning to handle diverse e‑commerce intents and resource constraints. Deployed on Taobao Pailitao, the system achieved significant online gains: +17.90% item page views, +27.04% transactions, and +8.94% gross merchandise value.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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