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Aryo Lotfi

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#artificial intelligence Preprint Sep 2026

On the Importance of Gating: Memorization vs. In-Context Learning in State Space Models

It is shown that this gating mechanism causes SSMs to first learn an in-weights"memorization"solution, while delaying, or even preventing, convergence to a correct in-context learning solution, and that gating is often beneficial for improving generalization to long sequence lengths.

W. Tong, Aryo Lotfi, Emmanuel Abbé et al. · 0 citations
Preprint Aug 2026

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve

It is suggested that using standard CoT prompting increasingly acts as a source of distraction as models grow stronger, because standard CoT prompting also demands style adaptation, formatting compliance, and potentially undesired contextualization, which can distract models from the core reasoning task.

Denys Pushkin, Albert Q. Jiang, Aryo Lotfi et al. · 0 citations

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