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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

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OPBench: A Graph Benchmark to Combat the Opioid Crisis

📝 Summary:
OPBench is the first comprehensive graph benchmark to systematically evaluate graph learning methods for the opioid crisis. It includes five diverse datasets across three domains and a unified framework, providing insights for future research.

🔹 Publication Date: Published on Feb 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.14602
• PDF: https://arxiv.org/pdf/2602.14602
• Github: https://github.com/Tianyi-Billy-Ma/OPBench

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For more data science resources:
https://t.iss.one/DataScienceT

#OpioidCrisis #GraphLearning #DataScience #MachineLearning #PublicHealth
Causal Concept Graphs in LLM Latent Space for Stepwise Reasoning

📝 Summary:
Causal Concept Graphs identify causal relationships between concepts in LLMs using sparse autoencoders and differentiable structure learning. This method significantly improves causal fidelity for multi-step reasoning over prior techniques, yielding sparse and stable graphs.

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10377
• PDF: https://arxiv.org/pdf/2603.10377

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For more data science resources:
https://t.iss.one/DataScienceT

#CausalAI #LLMs #MachineLearning #GraphLearning #ExplainableAI