Texo: Formula Recognition within 20M Parameters

TL;DR

This paper presents Texo, a minimalist yet highperformance formula recognition model that contains only 20 million parameters that enables real-time inference on consumer-grade hardware and even in-browser deployment.

Abstract

In this paper we present Texo, a minimalist yet highperformance formula recognition model that contains only 20 million parameters. By attentive design, distillation and transfer of the vocabulary and the tokenizer, Texo achieves comparable performance to state-of-the-art models such as UniMERNet-T and PPFormulaNet-S, while reducing the model size by 80% and 65%, respectively. This enables real-time inference on consumer-grade hardware and even in-browser deployment. We also developed a web application to demonstrate the model capabilities and facilitate its usage for end users.

Figures (2)

• Figure 1: Example images that Texo is able to recognize.
• Figure 2: Texo model architecture in the training process