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News/Convergent Evolution: How Different Language Models Learn Similar Number Representations
arxiv
PublishedApril 24, 2026 at 4:00 AM
—neutral

Convergent Evolution: How Different Language Models Learn Similar Number Representations

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2604.20817v1 Announce Type: cross Abstract: Language models trained on natural text learn to represent numbers using periodic features with dominant periods at $T=2, 5, 10$. In this paper, we identify a two-tiered hierarchy of these features: while Transformers, Linear RNNs, LSTMs, and classic

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Discussion
Mentioned models
04
  • 01
    Transformers
  • 02
    Linear RNNs
  • 03
    LSTMs
  • 04
    classical word embeddings
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#language models#feature learning#convergent evolution

No replies yet. Be first.

Mentioned models
04
  • 01
    Transformers
  • 02
    Linear RNNs
  • 03
    LSTMs
  • 04
    classical word embeddings
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#language models#feature learning#convergent evolution

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