Lower bounds on transformers with infinite precision

Alexander Kozachinskiy
12/28/2024
cs.LGcs.AIstat.ML

No confident code implementation found for this paper.

Abstract

In this note, we use the VC dimension technique to prove the first lower bound against one-layer softmax transformers with infinite precision. We do so for two tasks: function composition, considered by Peng, Narayanan, and Papadimitriou, and the SUM$_2$ task, considered by Sanford, Hsu, and Telgarsky.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{kozachinskiy2024lower,
  title  = {Lower bounds on transformers with infinite precision},
  author = {Alexander Kozachinskiy},
  year   = {2024},
  eprint = {2412.20195},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2412.20195v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2412.20195.svg)](https://codeofpaper.com/paper/2412.20195)

Discussion