# sustain.AI: a Recommender System to analyze Sustainability Reports

arXiv: https://arxiv.org/abs/2305.08711 · HTML: https://mlsanity.com/paper/2305.08711/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 17 references that are in the map.
- First posted on arXiv 15 May 2023.

## Builds on (most cited first, 4 of 4)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://mlsanity.com/paper/1506.01497/) (2015)
- [KPI-BERT: A Joint Named Entity Recognition and Relation Extraction Model for Financial Reports](https://mlsanity.com/paper/2208.02140/) (2022)
- [Towards automating Numerical Consistency Checks in Financial Reports](https://mlsanity.com/paper/2211.06112/) (2022)

## Built on by (most cited first, 3 of 3)

- [ML-Promise: A Multilingual Dataset for Corporate Promise Verification](https://mlsanity.com/paper/2411.04473/) (2024)
- [Pointer-Guided Pre-Training: Infusing Large Language Models with Paragraph-Level Contextual Awareness](https://mlsanity.com/paper/2406.04156/) (2024)
- [Towards Empowering Consumers through Sentence-level Readability Scoring in German ESG Reports](https://mlsanity.com/paper/2603.29861/) (2026)

## Abstract (arXiv)

We present sustainAI, an intelligent, context-aware recommender system that assists auditors and financial investors as well as the general public to efficiently analyze companies' sustainability reports. The tool leverages an end-to-end trainable architecture that couples a BERT-based encoding module with a multi-label classification head to match relevant text passages from sustainability reports to their respective law regulations from the Global Reporting Initiative (GRI) standards. We evaluate our model on two novel German sustainability reporting data sets and consistently achieve a significantly higher recommendation performance compared to multiple strong baselines. Furthermore, sustainAI is publicly available for everyone at https://sustain.ki.nrw/.