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Transformers can achieve Turing completeness without positional encoding

By PulseAugur Editorial · [3 sources] ·

Two new research papers explore the necessity of positional encoding (PE) in transformer models. One paper demonstrates that sliding-window transformers can achieve Turing completeness without PE, suggesting that the window mechanism itself provides sufficient positional information. The other paper investigates PE's role in Vision Transformers (ViTs), finding that while ViTs can develop spatial structure without PE, PEs anchor this structure and significantly improve robustness against content-disrupting distribution shifts. AI

IMPACT Challenges the necessity of positional encodings, potentially simplifying future transformer architectures and improving efficiency.

RANK_REASON Two academic papers published on arXiv discussing theoretical aspects of transformer architectures.

Read on Hugging Face Daily Papers →

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

Transformers can achieve Turing completeness without positional encoding

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COVERAGE [3]

  1. arXiv cs.LG TIER_1 English(EN) · Qian Li, Xinyu Mao, Shang-Hua Teng ·

    Rethinking the Role of Positional Encoding: Sliding-Window Transformers without PE Remain Turing Complete

    arXiv:2606.01532v1 Announce Type: new Abstract: Positional encoding (PE) is widely viewed as necessary for transformers to process ordered sequences: without them, the next-token map appears permutation-invariant in its context tokens. This intuition underlies all prior universal…

  2. arXiv cs.LG TIER_1 English(EN) · Mahmoud Mannes ·

    Positional Encodings Anchor Spatial Structure in Vision Transformers: A Geometric Perspective on Robustness

    arXiv:2606.00124v1 Announce Type: cross Abstract: Positional embeddings (PEs) in Vision Transformers (ViTs) are known to impact performance and robustness, but their role in shaping internal spatial representations is not well understood. In this work, we study how different form…

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

    Rethinking the Role of Positional Encoding: Sliding-Window Transformers without PE Remain Turing Complete

    Positional encoding (PE) is widely viewed as necessary for transformers to process ordered sequences: without them, the next-token map appears permutation-invariant in its context tokens. This intuition underlies all prior universality results, which rely on positional informatio…

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