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Renmin University of China
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Bridging the gap between transient experience and persistent capabilities, SPEE enables LLMs to self-improve by evolving their knowledge through a unique experience distillation process.
Cross-sample consistency regularization can eliminate feature fragmentation in Sparse Autoencoders, leading to more reliable and interpretable latent representations.
