10.1k citations · 12.1k across the 55 of their papers we have counts for
7 papers · 1 filter
Graph Stochastic Neural Process for Inductive Few-shot Knowledge Graph Completion
Zicheng Zhao, Linhao Luo, Shirui Pan +2
Knowledge graphs (KGs) store enormous facts as relationships between entities. Due to the long-tailed distribution of relations and the incompleteness of KGs, there is growing inte…
Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach
Zhiwei Li, Guodong Long, Tianyi Zhou +2
Federated Collaborative Filtering (FedCF) is an emerging field focused on developing a new recommendation framework with preserving privacy in a federated setting. Existing FedCF m…
Navigating the Future of Federated Recommendation Systems with Foundation Models
Zhiwei Li, Guodong Long, Chunxu Zhang +3
Federated Recommendation Systems (FRSs) offer a privacy-preserving alternative to traditional centralized approaches by decentralizing data storage. However, they face persistent c…
Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models
Shengchao Chen, Guodong Long, Jing Jiang +1
This paper demonstrates that pre-trained language models (PLMs) are strong foundation models for on-device meteorological variables modeling. We present LM-Weather, a generic appro…
Personalized Additive Modeling for Multi-level Federated Learning
Shutong Chen, Guodong Long, Tianyi Zhou +3
Contemporary AI faces the challenge of balancing generality with user-specific personalization. In federated learning (FL), this challenge is amplified by highly heterogeneous clie…
What Hides behind Unfairness? Exploring Dynamics Fairness in Reinforcement Learning
Zhihong Deng, Jing Jiang, Guodong Long +1
In sequential decision-making problems involving sensitive attributes like race and gender, reinforcement learning (RL) agents must carefully consider long-term fairness while maxi…
Seeing Text in the Dark: Algorithm and Benchmark
Chengpei Xu, Hao Fu, Long Ma +6
Localizing text in low-light environments is challenging due to visual degradations. Although a straightforward solution involves a two-stage pipeline with low-light image enhancem…