#dynamic-graphs2 articles

2 articles

AINeutralarXiv – CS AI · 15h ago7/10

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LLMTM: Benchmarking and Optimizing LLMs for Temporal Motif Analysis in Dynamic Graphs

Researchers introduced LLMTM, a comprehensive benchmark to evaluate Large Language Models' performance on temporal motif analysis in dynamic graphs. The study tested nine different LLMs and developed a structure-aware dispatcher that balances accuracy with cost-effectiveness for graph analysis tasks.

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AINeutralarXiv – CS AI · Feb 274/103

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DyGnROLE: Modeling Asymmetry in Dynamic Graphs with Node-Role-Oriented Latent Encoding

Researchers introduce DyGnROLE, a new AI architecture that better models directed dynamic graphs by treating source and destination nodes differently. The system uses role-specific embeddings and a self-supervised learning approach called Temporal Contrastive Link Prediction to achieve superior performance on future edge classification tasks.

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