New research suggests transformers are inherently succinct in representing concepts.

作者 PulseAugur 编辑部 · [2 个来源] · 2026-04-25 21:33

A new paper introduces succinctness as a metric for evaluating the expressive power of transformer models. Researchers demonstrated that transformers can represent formal languages more concisely than traditional methods like finite automata and LTL formulas. This high expressivity implies that verifying properties of transformers is computationally intractable, specifically EXPSPACE-complete. AI

影响 Introduces a new theoretical framework for analyzing transformer expressivity, with implications for understanding model capabilities and limitations.

排序理由 Academic paper introducing a new theoretical concept and analysis of transformer models.

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报道来源 [2]

Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] · 2026-04-26 14:20

Transformers are Inherently Succinct https:// lobste.rs/s/hzhyw9 # ai https:// arxiv.org/abs/2510.19315

Transformers are Inherently Succinct https:// lobste.rs/s/hzhyw9 # ai https:// arxiv.org/abs/2510.19315

链接 lobste.rs/…/hzhyw9 arxiv.org/…/2510.19315
Lobsters — AI tag TIER_1 English(EN) · arxiv.org via aphaelion · 2026-04-25 21:33

Transformers are Inherently Succinct

<p>Abstract: We propose succinctness as a measure of the expressive power of a transformer in describing a concept. To this end, we prove that transformers are highly expressive in that they can represent formal languages substantially more succinctly than standard representation…

报道来源 [2]

Transformers are Inherently Succinct https:// lobste.rs/s/hzhyw9 # ai https:// arxiv.org/abs/2510.19315

Transformers are Inherently Succinct

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