activity
20172026
most citedCooperative Training of Deep Aggregation Networks for RGB-D Action Recognition

42 citations · 231 across the 61 of their papers we have counts for

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6 papers · 1 filter

cs.AI2026

SpaCellAgent: A Self-Evolving LLM-Based Multi-Agent Framework for Trajectory Analysis

Songhan Wang, Haoang Chi, He Li +6

Spatial and Single-cell transcriptomics are transformative in deciphering cellular dynamics. As the fundamental paradigm for reconstructing cell developmental paths, trajectory inf…

cs.AI2023

Structure Guided Multi-modal Pre-trained Transformer for Knowledge Graph Reasoning

Ke Liang, Sihang Zhou, Yue Liu +3

Multimodal knowledge graphs (MKGs), which intuitively organize information in various modalities, can benefit multiple practical downstream tasks, such as recommendation systems, a…

cs.AI2023

Medical Federated Model with Mixture of Personalized and Sharing Components

Yawei Zhao, Qinghe Liu, Xinwang Liu +1

Although data-driven methods usually have noticeable performance on disease diagnosis and treatment, they are suspected of leakage of privacy due to collecting data for model train…

cs.AI2023

arXiv4TGC: Large-Scale Datasets for Temporal Graph Clustering

Meng Liu, Ke Liang, Yue Liu +3

Temporal graph clustering (TGC) is a crucial task in temporal graph learning. Its focus is on node clustering on temporal graphs, and it offers greater flexibility for large-scale…

cs.AI2023

Message Intercommunication for Inductive Relation Reasoning

Ke Liang, Lingyuan Meng, Sihang Zhou +5

Inductive relation reasoning for knowledge graphs, aiming to infer missing links between brand-new entities, has drawn increasing attention. The models developed based on Graph Ind…

cs.AI2023

Revisiting Initializing Then Refining: An Incomplete and Missing Graph Imputation Network

Wenxuan Tu, Bin Xiao, Xinwang Liu +3

With the development of various applications, such as social networks and knowledge graphs, graph data has been ubiquitous in the real world. Unfortunately, graphs usually suffer f…