Author

Toni J. B. Liu

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#artificial intelligence Preprint Sep 2026

Causal and Interpretable Structures in LLM Compositional Tasks

This work studies activations from ensembles of prompts that require inferring relationships between three tokens corresponding to a cyclic concept to correctly predict the next token and finds a consistent layerwise progression in how the joint dependence among the tokens is geometrically organized and causally used.

Gurbir Arora, To-Ni J. B. Liu, Jiajun Bao et al. · 0 citations

#artificial intelligence Preprint Sep 2026

The Geometry of Ignorance: LLMs Know When to Temper Bayesian Priors

The direction of ignorance is causally active: raising or lowering $\lambda$ at the final prediction state steers the prediction toward or away from the unigram prior in KL divergence, with larger models generally exhibiting lower prior reliance in the high-context limit.

To-Ni J. B. Liu, Jiajun Bao, Yizhou Liu et al. · 0 citations