Reward-informed sparse autoencoders and the solution-completeness confound
Read the original at arxiv.org→arXiv:2608.26136v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) decompose language-model activations into sparse, interpretable features, and an appealing way to aim them at reasoning is to curate their...
Original headline: "Reward-Informed Sparse Autoencoders and the Solution-Completeness Confound"
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- Aug 28, 04:00 UTC arXiv cs.CL lead source Reward-Informed Sparse Autoencoders and the Solution-Completeness Confound