LLMs represent numbers on a helix and manipulate that helix to do addition.
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Updated
Feb 4, 2025 - Jupyter Notebook
#
mechanistic-inter
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Cross-modal SAE interpretability: are sparse features causally tied to a foundation model's self-difficulty? Tested identically on Pythia (LLM) and Chronos-T5 (time-series), predictive null in both, causal signal in the LM only.
reproducible-research chronos pythia uncertainty-quantification sae interpretability sparse-autoencoder time-series-forecasting foundation-models selective-prediction llms mechanistic-inter
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Updated
Jun 9, 2026 - Python
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