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New theory explains transformer generalization via Fourier Spectra

By PulseAugur Editorial · [3 sources] ·

Researchers have developed a new theoretical framework to understand how transformers generalize, focusing on the Fourier Spectra of their target functions. This approach utilizes PAC-Bayes theory to derive generalization bounds, contrasting with previous methods based on Rademacher complexity. The study demonstrates that sparse spectra concentrated on low-degree components facilitate low-sharpness constructions with strong generalization properties, supported by empirical evaluations and interpretability studies. AI

IMPACT Provides a new theoretical lens for understanding and potentially improving transformer generalization capabilities.

RANK_REASON The cluster contains an academic paper detailing theoretical research on transformer generalization.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

New theory explains transformer generalization via Fourier Spectra

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The cluster contains an academic paper detailing theoretical research on transformer generalization.
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COVERAGE [3]

  1. arXiv cs.AI TIER_1 English(EN) · Paul Lintilhac, Sair Shaikh ·

    A Sharper Picture of Generalization in Transformers

    arXiv:2605.20988v1 Announce Type: cross Abstract: We study transformers' generalization behavior on boolean domains from the perspective of the Fourier Spectra of their target functions. In contrast to prior work (Edelman et al., 2022; Trauger and Tewari, 2024), which derived gen…

  2. arXiv cs.AI TIER_1 English(EN) · Sair Shaikh ·

    A Sharper Picture of Generalization in Transformers

    We study transformers' generalization behavior on boolean domains from the perspective of the Fourier Spectra of their target functions. In contrast to prior work (Edelman et al., 2022; Trauger and Tewari, 2024), which derived generalization bounds from Rademacher complexity, we …

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    A Sharper Picture of Generalization in Transformers

    We study transformers' generalization behavior on boolean domains from the perspective of the Fourier Spectra of their target functions. In contrast to prior work (Edelman et al., 2022; Trauger and Tewari, 2024), which derived generalization bounds from Rademacher complexity, we …

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