millioniron/LLM_exploration_Graph-Attention-Mechanisms-Perspective
Code: Attention Mechanisms Perspective: Exploring LLM Processing of Graph-Structured Data (ICML2025)
This project helps researchers and developers understand how Large Language Models (LLMs) process information that is structured like a network or graph (e.g., social networks, molecular structures). It takes graph-structured data and applies different attention mechanisms within LLMs to show how they interpret and learn from these connections. The primary users are AI/ML researchers or practitioners working on advanced LLM applications, especially those involving complex relational data.
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Use this if you are a machine learning researcher or engineer interested in the underlying mechanisms of how LLMs handle graph-structured data and want to experiment with different attention strategies.
Not ideal if you are looking for a plug-and-play solution for a specific graph-based prediction task or if you do not have a strong background in machine learning and LLM architectures.
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May 09, 2025
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