arxiv
PublishedJune 1, 2026 at 4:00 AM
—neutral
Discovering a Zeta Map Algorithm on Dyck Paths via Mechanistic Interpretability
Publisher summary· verbatim
arXiv:2605.30482v1 Announce Type: new Abstract: Machine learning is increasingly used in mathematical discovery, but in mathematics the desired output is often not a prediction itself, but an explicit construction that can be checked independently. We study this setting through the zeta map on Dyck
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivCSWBench: Evaluating Context-Sensitive Code-Switching in Creative Writing3harxivFireGraphNet: Sub-daily wildfire spread prediction with directed graph neural networks3harxivNarrowing the Collaboration Gap, Probably3harxivRiding the Fixed-Point Curve: Image Classification in the Continuous Thought Machine3hThe Bubble Brief
MON · WED · FRIRead AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗