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Seeing in Pangram Space

Quality: 9/10 Relevance: 9/10

Summary

Pangram Labs presents an interpretability study of Pangram 3.3.2, analyzing internal activations and embedding space to understand how AI-generated and human-authored texts are represented across layers. The work highlights that model internals encode detectable patterns beyond the final detection score, including model-family clustering and humanizer effects.

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