2 citations · 2 across the 7 of their papers we have counts for
7 papers
Efficient Learning-based Graph Simulation for Temporal Graphs
Sheng Xiang, Chenhao Xu, Dawei Cheng +2
Graph simulation has recently received a surge of attention in graph processing and analytics. In real-life applications, e.g. social science, biology, and chemistry, many graphs a…
DHG-Bench: A Comprehensive Benchmark for Deep Hypergraph Learning
Fan Li, Xiaoyang Wang, Wenjie Zhang +2
Deep graph models have achieved great success in network representation learning. However, their focus on pairwise relationships restricts their ability to learn pervasive higher-o…
MMAPG: A Training-Free Framework for Multimodal Multi-hop Question Answering via Adaptive Planning Graphs
Yiheng Hu, Xiaoyang Wang, Qing Liu +4
Multimodal Multi-hop question answering requires integrating information from diverse sources, such as images and texts, to derive answers. Existing methods typically rely on seque…
Parallel-R1: Towards Parallel Thinking via Reinforcement Learning
Tong Zheng, Hongming Zhang, Wenhao Yu +7
Parallel thinking has emerged as a novel approach for enhancing the reasoning capabilities of large language models (LLMs) by exploring multiple reasoning paths concurrently. Howev…
Efficient Dynamic Attributed Graph Generation
Fan Li, Xiaoyang Wang, Dawei Cheng +3
Data generation is a fundamental research problem in data management due to its diverse use cases, ranging from testing database engines to data-specific applications. However, rea…
Parallel Higher-order Truss Decomposition
Chen Chen, Jingya Qian, Hui Luo +2
The k-truss model is one of the most important models in cohesive subgraph analysis. The k-truss decomposition problem is to compute the trussness of each edge in a given graph, an…