SemaCDR builds a unified semantic space with LLM-generated domain-agnostic features and adaptive fusion to improve cross-domain sequential recommendations over baselines.
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MBGR is a new generative recommendation framework using business-aware semantic IDs, multi-business prediction, and label dynamic routing to handle multiple businesses without seesaw effects or representation confusion, validated by experiments and deployed at Meituan.
A2Gen models temporal user action sequences with context-aware attention and autoregressive generation to improve short video recommendation accuracy, showing gains in watch time and retention on large-scale tests.
citing papers explorer
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SemaCDR: LLM-Powered Transferable Semantics for Cross-Domain Sequential Recommendation
SemaCDR builds a unified semantic space with LLM-generated domain-agnostic features and adaptive fusion to improve cross-domain sequential recommendations over baselines.
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MBGR: Multi-Business Prediction for Generative Recommendation at Meituan
MBGR is a new generative recommendation framework using business-aware semantic IDs, multi-business prediction, and label dynamic routing to handle multiple businesses without seesaw effects or representation confusion, validated by experiments and deployed at Meituan.
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Action-Aware Generative Sequence Modeling for Short Video Recommendation
A2Gen models temporal user action sequences with context-aware attention and autoregressive generation to improve short video recommendation accuracy, showing gains in watch time and retention on large-scale tests.