Author

Yury Polyanskiy

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#artificial intelligence May 2026

Scaling Limits of Long-Context Transformers

It is shown that the critical scale at which selectivity emerges is determined by the local exponent of the distance-to-query distribution near zero rather than by global features of the context, and scales like $\beta_n^\ast \asymp n^{2/(d-1)}$ for uniform keys on $\mathbb{S}^{d-1}$.

Giuseppe Bruno, Shi Chen, Zheng-Jiang Lin et al. · arXiv.org · 3 citations

#machine learning May 2026

Continuous First, Discrete Later: VQ-VAEs Without Dimensional Collapse

Theoretical analysis predicts downstream performance as a function of warm-up length, enabling an adaptive criterion for switching from AE Warm-up to VQ-VAE training and empirically characterize how warm-up duration governs the achievable final loss.

Xinyu Zhao, N. Karagodin, Hamed Hassani et al. · arXiv.org · 0 citations