# Stringological sequence prediction II: Right-to-left automaticity and related complexity measures

arXiv: https://arxiv.org/abs/2607.17369 · HTML: https://mlsanity.com/paper/2607.17369/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 18 references that are in the map.
- First posted on arXiv 19 Jul 2026.

## Builds on (most cited first, 3 of 3)

- [Bayesian Context Trees: Modelling and exact inference for discrete time series](https://mlsanity.com/paper/2007.14900/) (2020)
- [Learning to Answer from Correct Demonstrations](https://mlsanity.com/paper/2510.15464/) (2025)
- [Stringological sequence prediction I: efficient algorithms for predicting highly repetitive sequences](https://mlsanity.com/paper/2603.26852/) (2026)

## Abstract (arXiv)

In a previous paper, we began the study of sequence prediction algorithms adapted to stringological word complexity measures. One measure we considered was left-to-right (most-significant-digit-first) automaticity. Here, we show a statistically and computationally efficient algorithm adapted to the ``dual'' right-to-left (least-significant-digit-first) automaticity, which turns out to be substantially different for our purpose. We also demonstrate a prediction algorithm for a more expressive measure that we call ``arithmetic repetition complexity''. In particular, the latter can be used for predicting the so-called mix-automatic sequences.