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20222026
most citedGenerative Pretrained Hierarchical Transformer for Time Series Forecasting

37 citations · 90 across the 18 of their papers we have counts for

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7 papers · 1 filter

cs.IR2026

KuaiSearch: An E-Commerce Search Dataset with Authentic Queries and Product Texts for Recall, Ranking, and Relevance

Yupeng Li, Ben Chen, Mingyue Cheng +7

E-commerce search connects user needs with massive product inventories, yet real-world systems face challenges from ambiguous queries, noisy product texts, and diverse user prefere…

cs.IR2025

Towards Context-aware Reasoning-enhanced Generative Searching in E-commerce

Zhiding Liu, Ben Chen, Mingyue Cheng +6

Search-based recommendation is one of the most critical application scenarios in e-commerce platforms. Users' complex search contexts--such as spatiotemporal factors, historical in…

cs.IR2025

FlowRec: Prior-Informed Flow Matching for Efficient Sequential Recommendation Generation

Li Li, Mingyue Cheng, Yuyang Ye +2

Sequential recommendation aims to predict each user's next preferred item based on their historical interactions. Recently, diffusion-based approaches have demonstrated strong gene…

cs.IR2024

Pre-trained Language Model and Knowledge Distillation for Lightweight Sequential Recommendation

Li Li, Mingyue Cheng, Zhiding Liu +3

Sequential recommendation models user interests based on historical behaviors to provide personalized recommendation. Previous sequential recommendation algorithms primarily employ…

cs.IR2023★ 1 cited

Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems

Hao Zhang, Mingyue Cheng, Zhiding Liu +1

Sequential recommender systems (SRS) have gained increasing popularity due to their remarkable proficiency in capturing dynamic user preferences. In the current setup of SRS, a com…

cs.IR2023

Reformulating Sequential Recommendation: Learning Dynamic User Interest with Content-enriched Language Modeling

Junzhe Jiang, Shang Qu, Mingyue Cheng +8

Recommender systems are indispensable in the realm of online applications, and sequential recommendation has enjoyed considerable prevalence due to its capacity to encapsulate the…

cs.IR2022★ 10 cited

One Person, One Model--Learning Compound Router for Sequential Recommendation

Zhiding Liu, Mingyue Cheng, Zhi Li +2

Deep learning has brought significant breakthroughs in sequential recommendation (SR) for capturing dynamic user interests. A series of recent research revealed that models with mo…