7 papers · 1 filter
IntHQ: Task-Interactive Hierarchical Query on Dual-Stream Representations for Generative Recommendation
Junjie Sun, Longfei Xu, Huimin Yan +3
Multi-task learning over heterogeneous data is fundamental to modern recommendation, while generative models are emerging as the backbone of next-generation recommenders. However,…
SCASRec: A Self-Correcting and Auto-Stopping Model for Generative Route List Recommendation
Chao Chen, Longfei Xu, Daohan Su +5
Route recommendation systems commonly adopt a multi-stage pipeline involving fine-ranking and re-ranking to produce high-quality ordered recommendations. However, this paradigm fac…
IntRR: A Framework for Integrating SID Redistribution and Length Reduction
Zesheng Wang, Longfei Xu, Weidong Deng +3
Generative Recommendation (GR) has emerged as a transformative paradigm that reformulates the traditional cascade ranking system into a sequence-to-item generation task, facilitate…
IntTravel: A Real-World Dataset and Generative Framework for Integrated Multi-Task Travel Recommendation
Huimin Yan, Longfei Xu, Junjie Sun +4
Next Point of Interest (POI) recommendation is essential for modern mobility and location-based services. To provide a smooth user experience, models must understand several compon…
Towards Full Candidate Interaction: A Comprehensive Comparison Network for Better Route Recommendation
Hanyu Guo, Chao Chen, Longfei Xu +3
We argue that the decision-making essence of route recommendation is comparative judgment: users choose a route because it is better than alternatives in specific aspects. The deci…
IntSR: An Integrated Generative Framework for Search and Recommendation
Huimin Yan, Longfei Xu, Junjie Sun +6
Generative recommendation has emerged as a promising paradigm, demonstrating remarkable results in both academic benchmarks and industrial applications. However, existing systems p…