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TopicsSparse Autoencoders AI Scientific Discovery Large language models

On HEADLINES, Yelp, and Congress, sparse-autoencoder methods yield more significant hypotheses than LLM and topic-model baselines.

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On three real-world tasks, 45/60 hypotheses generated by our method are significant, compared to at most 24 for the baselines.

Sparse Autoencoders for Hypothesis Generationpreprintextraction 0.80

Movva, Rajiv et al. · arXiv.org · Feb 5, 2025 · original

Real-world tasks: HEADLINES, YELP, CONGRESS; significance by Bonferroni-corrected multivariate regression on heldout data.

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