15 papers
Beyond Model Base Retrieval: Weaving Knowledge to Master Fine-grained Neural Network Design
Jialiang Wang, Hanmo Liu, Shimin Di +4
Designing high-performance neural networks for new tasks requires balancing optimization quality with search efficiency. Current methods fail to achieve this balance: neural archit…
Intent Propagation Contrastive Collaborative Filtering
Haojie Li, Junwei Du, Guanfeng Liu +3
Disentanglement techniques used in collaborative filtering uncover interaction intents between nodes, improving the interpretability of node representations and enhancing recommend…
ID and Graph View Contrastive Learning with Multi-View Attention Fusion for Sequential Recommendation
Xiaofan Zhou, Kyumin Lee
Sequential recommendation has become increasingly prominent in both academia and industry, particularly in e-commerce. The primary goal is to extract user preferences from historic…
Proficient Graph Neural Network Design by Accumulating Knowledge on Large Language Models
Jialiang Wang, Hanmo Liu, Shimin Di +4
High-level automation is increasingly critical in AI, driven by rapid advances in large language models (LLMs) and AI agents. However, LLMs, despite their general reasoning power,…
Trajectory Data Management and Mining: A Survey from Deep Learning to the LLM Era
Wei Chen, Yuanshao Zhu, Yanchuan Chang +11
Trajectory computing is a pivotal domain encompassing trajectory data management and mining, garnering widespread attention due to its crucial role in various practical application…
CroTad: A Contrastive Reinforcement Learning Framework for Online Trajectory Anomaly Detection
Rui Xue, Dan He, Fengmei Jin +2
Detecting trajectory anomalies is a vital task in modern Intelligent Transportation Systems (ITS), enabling the identification of unsafe, inefficient, or irregular travel behaviour…