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ENTITY Reward-Informed Sparse Autoencoder

Reward-Informed Sparse Autoencoder

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    Sparse autoencoders show reward filtering captures solution completeness, not reasoning quality

    Researchers have developed a reward-informed sparse autoencoder (RI-SAE) to interpret language model activations, specifically focusing on reasoning capabilities. While the RI-SAE successfully separated high-reward and …