24 citations · 27 across the 14 of their papers we have counts for
15 papers
Empowering Cross-Domain Sequential Recommendation with Hybrid Tokenization and Serial-Parallel Decoding
Yuxuan Hu, Yuhao Wang, Tianbo Huang +4
Cross-domain sequential recommendation (CDSR) aims to model users' dynamic interest transitions and sequential patterns across multiple domains. Recently, generative recommendation…
T-GINEE: A Tensor-Based Multilayer Graph Representation Learning
Maolin Wang, Ziting Mai, Xuhui Chen +9
Traditional network analysis focuses on single-layer networks, real-world systems often form multilayer networks with multiple relationship types. However, existing methods typical…
The Best of the Two Worlds: Harmonizing Semantic and Hash IDs for Sequential Recommendation
Ziwei Liu, Yejing Wang, Wanyu Wang +6
Conventional Sequential Recommender Systems (SRS) typically assign unique hash IDs (HID) to construct item embeddings, which mainly capture collaborative signals from historical us…
MTA: A Merge-then-Adapt Framework for Personalized Large Language Model
Xiaopeng Li, Yuanjin Zheng, Wanyu Wang +6
Personalized Large Language Models (PLLMs) aim to align model outputs with individual user preferences, a crucial capability for user-centric applications. However, the prevalent a…
Emotion and Intention Guided Multi-Modal Learning for Sticker Response Selection
Yuxuan Hu, Jian Chen, Yuhao Wang +6
Stickers are widely used in online communication to convey emotions and implicit intentions. The Sticker Response Selection (SRS) task aims to select the most contextually appropri…
LLM-EDT: Large Language Model Enhanced Cross-domain Sequential Recommendation with Dual-phase Training
Ziwei Liu, Qidong Liu, Wanyu Wang +6
Cross-domain Sequential Recommendation (CDSR) has been proposed to enrich user-item interactions by incorporating information from various domains. Despite current progress, the im…
GFlowGR: Fine-tuning Generative Recommendation Frameworks with Generative Flow Networks
Yejing Wang, Shengyu Zhou, Jinyu Lu +9
Generative recommendations (GR), which usually include item tokenizers and generative Large Language Models (LLMs), have demonstrated remarkable success across a wide range of scen…
Bridge the Domains: Large Language Models Enhanced Cross-domain Sequential Recommendation
Qidong Liu, Xiangyu Zhao, Yejing Wang +6
Cross-domain Sequential Recommendation (CDSR) aims to extract the preference from the user's historical interactions across various domains. Despite some progress in CDSR, two prob…
Behavior Modeling Space Reconstruction for E-Commerce Search
Yejing Wang, Chi Zhang, Xiangyu Zhao +8
Delivering superior search services is crucial for enhancing customer experience and driving revenue growth. Conventionally, search systems model user behaviors by combining user p…
Large Language Model Enhanced Recommender Systems: A Survey
Qidong Liu, Xiangyu Zhao, Yuhao Wang +9
Large Language Model (LLM) has transformative potential in various domains, including recommender systems (RS). There have been a handful of research that focuses on empowering the…
SIGMA: Selective Gated Mamba for Sequential Recommendation
Ziwei Liu, Qidong Liu, Yejing Wang +6
In various domains, Sequential Recommender Systems (SRS) have become essential due to their superior capability to discern intricate user preferences. Typically, SRS utilize transf…
BiVRec: Bidirectional View-based Multimodal Sequential Recommendation
Jiaxi Hu, Jingtong Gao, Xiangyu Zhao +6
The integration of multimodal information into sequential recommender systems has attracted significant attention in recent research. In the initial stages of multimodal sequential…
MLPST: MLP is All You Need for Spatio-Temporal Prediction
Zijian Zhang, Ze Huang, Zhiwei Hu +6
Traffic prediction is a typical spatio-temporal data mining task and has great significance to the public transportation system. Considering the demand for its grand application, w…
Rethinking Sensors Modeling: Hierarchical Information Enhanced Traffic Forecasting
Qian Ma, Zijian Zhang, Xiangyu Zhao +5
With the acceleration of urbanization, traffic forecasting has become an essential role in smart city construction. In the context of spatio-temporal prediction, the key lies in ho…
PromptST: Prompt-Enhanced Spatio-Temporal Multi-Attribute Prediction
Zijian Zhang, Xiangyu Zhao, Qidong Liu +6
In the era of information explosion, spatio-temporal data mining serves as a critical part of urban management. Considering the various fields demanding attention, e.g., traffic st…