# A Linear Temporal Logic of Frequencies on Series of Events

arXiv: https://arxiv.org/abs/2604.10669 · HTML: https://mlsanity.com/paper/2604.10669/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Apr 2026.

## Built on by (most cited first, 1 of 1)

- [Counting Worlds Branching Time Semantics for post-hoc Bias Mitigation in generative AI](https://mlsanity.com/paper/2604.19431/) (2026)

## Abstract (arXiv)

This paper introduces LTLF, a temporal logic designed to express the frequency properties of event series in a natural but rigorous manner. By introducing novel, measure-sensitive operators, LTLF allows for the evaluation of frequencies and the prediction of future occurrences, thus providing a formal framework to monitor and control quantitative systems, such as machine learning classifiers. The core novelty lies in the introduction of original modal quantifiers associated with a standard Kripke-style semantics. These quantifiers enable the explicit formalization of event series properties and the investigation of the relationship between actual observed frequencies and ideal distributions within a single logical structure. This framework bridges the gap between formal logical reasoning and empirical observation.