194 citations · 403 across the 49 of their papers we have counts for
22 papers · 1 filter
OneTrans: Unified Feature Interaction and Sequence Modeling with One Transformer in Industrial Recommender
Zhaoqi Zhang, Haolei Pei, Jun Guo +5
In recommendation systems, scaling up feature-interaction modules (e.g., Wukong, RankMixer) or user-behavior sequence modules (e.g., LONGER) has achieved notable success. However,…
A Survey of Real-World Recommender Systems: Challenges, Constraints, and Industrial Perspectives
Kuan Zou, Aixin Sun
Recommender systems have generated tremendous value for both users and businesses, drawing significant attention from academia and industry alike. However, due to practical constra…
Does Multimodality Improve Recommender Systems as Expected? A Critical Analysis and Future Directions
Hongyu Zhou, Yinan Zhang, Aixin Sun +1
Multimodal recommendation systems are increasingly popular for their potential to improve performance by integrating diverse data types. However, the actual benefits of this integr…
Towards Storage-Efficient Visual Document Retrieval: An Empirical Study on Reducing Patch-Level Embeddings
Yubo Ma, Jinsong Li, Yuhang Zang +8
Despite the strong performance of ColPali/ColQwen2 in Visualized Document Retrieval (VDR), it encodes each page into multiple patch-level embeddings and leads to excessive memory u…
Knowledge-Enhanced Conversational Recommendation via Transformer-based Sequential Modelling
Jie Zou, Aixin Sun, Cheng Long +1
In conversational recommender systems (CRSs), conversations usually involve a set of items and item-related entities or attributes, e.g., director is a related entity of a movie. T…
Hesitation and Tolerance in Recommender Systems
Kuan Zou, Aixin Sun, Yitong Ji +5
Users' interactions with recommender systems often involve more than simple acceptance or rejection. We highlight two overlooked states: hesitation, when people deliberate without…