Explaining the Reasoning of Large Language Models Using Attribution Graphs
Published:Dec 17, 2025 18:15
•1 min read
•ArXiv
Analysis
This article, sourced from ArXiv, focuses on the interpretability of Large Language Models (LLMs). It proposes a method using attribution graphs to understand the reasoning process within these complex models. The core idea is to visualize and analyze how different parts of the model contribute to a specific output. This is a crucial area of research as it helps to build trust and identify potential biases in LLMs.
Key Takeaways
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