Predictability in human mobility: From individual to collective (vision paper)
Human mobility is the foundation of urban dynamics and its prediction significantly benefits
various downstream location-based services. Nowadays, while deep learning approaches …
various downstream location-based services. Nowadays, while deep learning approaches …
A general tail item representation enhancement framework for sequential recommendation
Recently advancements in deep learning models have significantly facilitated the
development of sequential recommender systems (SRS). However, the current deep model …
development of sequential recommender systems (SRS). However, the current deep model …
Upper bound on the predictability of rating prediction in recommender systems
The task of rating prediction has undergone extensive scrutiny, employing diverse modeling
approaches to enhance accuracy. However, it remains uncertain whether a maximum …
approaches to enhance accuracy. However, it remains uncertain whether a maximum …
Limits of predictability in top-N recommendation
Top-N recommendation systems aim to recommend a small group of N items to users from
many products, and the accuracy of the system is a commonly used metric to evaluate its …
many products, and the accuracy of the system is a commonly used metric to evaluate its …
SynthoMinds: Bridging human programming intuition with retrieval, analogy, and reasoning in program synthesis
Q Gou, Y Dong, Q Ke - Journal of Systems and Software, 2024 - Elsevier
Program synthesis revolutionizes software development by automatically generating
executable programs based on given specifications. An emerging trend is to augment …
executable programs based on given specifications. An emerging trend is to augment …
Reduced implication-bias logic loss for neuro-symbolic learning
Integrating logical reasoning and machine learning by approximating logical inference with
differentiable operators is a widely used technique in the field of Neuro-Symbolic Learning …
differentiable operators is a widely used technique in the field of Neuro-Symbolic Learning …
InteractNet: Social Interaction Recognition for Semantic-rich Videos
The overwhelming surge of online video platforms has raised an urgent need for social
interaction recognition techniques. Compared with simple short-term actions, long-term …
interaction recognition techniques. Compared with simple short-term actions, long-term …
Cross-Grained Neural Collaborative Filtering for Recommendation
Collaborative Filtering has achieved great success in capturing users' preferences over
items. However, existing techniques only consider limited collaborative signals, leading to …
items. However, existing techniques only consider limited collaborative signals, leading to …