What Formal Languages Can Transformers Express? A Survey
November 01, 2023 ยท Declared Dead ยท ๐ Transactions of the Association for Computational Linguistics
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Authors
Lena Strobl, William Merrill, Gail Weiss, David Chiang, Dana Angluin
arXiv ID
2311.00208
Category
cs.LG: Machine Learning
Cross-listed
cs.CL,
cs.FL,
cs.LO
Citations
107
Venue
Transactions of the Association for Computational Linguistics
Last Checked
4 months ago
Abstract
As transformers have gained prominence in natural language processing, some researchers have investigated theoretically what problems they can and cannot solve, by treating problems as formal languages. Exploring such questions can help clarify the power of transformers relative to other models of computation, their fundamental capabilities and limits, and the impact of architectural choices. Work in this subarea has made considerable progress in recent years. Here, we undertake a comprehensive survey of this work, documenting the diverse assumptions that underlie different results and providing a unified framework for harmonizing seemingly contradictory findings.
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