# Read, Extract, Classify: A Tool for Smarter Requirements Engineering

arXiv: https://arxiv.org/abs/2605.11045 · HTML: https://mlsanity.com/paper/2605.11045/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 6 references that are in the map.
- First posted on arXiv 11 May 2026.

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

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [A Supervised Learning Approach For Heading Detection](https://mlsanity.com/paper/1809.01477/) (2018)
- [Adaptive Fine-Tuning of Transformer-Based Language Models for Named Entity Recognition](https://mlsanity.com/paper/2202.02617/) (2022)

## Abstract (arXiv)

This paper presents the ReXCL tool, which automates the extraction and classification processes in requirements engineering, enhancing the software development life-cycle. The tool features two main modules: Extraction, which processes raw requirement documents into a predefined schema using heuristics and predictive modeling, and Classification, which assigns class labels to requirements using adaptive fine-tuning of encoder-based models. The final output can be exported to external requirement engineering tools. Performance evaluations indicate that ReXCL significantly improves efficiency and accuracy in managing requirements, marking a novel approach to automating the schematization of semi-structured requirement documents.