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#model-interpretation News & Analysis

2 articles tagged with #model-interpretation. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles
AINeutralarXiv – CS AI · Jun 26/10
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TN-SHAP-G: Graph-Structured Tensor Network Surrogates for Shapley Values and Interactions

Researchers introduce TN-SHAP-G, a machine learning framework that efficiently computes Shapley values—a key method for explaining AI model decisions—by leveraging graph structure in data. The approach uses tensor networks to create compact surrogates that scale to larger datasets where traditional methods become computationally infeasible.

AINeutralarXiv – CS AI · Mar 96/10
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Position: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!

This position paper argues against anthropomorphizing intermediate tokens generated by language models as 'reasoning traces' or 'thoughts'. The authors contend that treating these computational outputs as human-like thinking processes is misleading and potentially harmful to AI research and understanding.