# ESGBench: A Benchmark for Explainable ESG Question Answering in Corporate Sustainability Reports

Source: [ESGBench: A Benchmark for Explainable ESG Question Answering in Corporate Sustainability Reports](<https://www.sota2.com/research/paper/691ff1fed6b0dd334292e5f1>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-11-22T05:01:45.247Z

Authors: Sherine George, Nithish Saji

Published: 2025-11-20T15:07:17.000Z

## Abstract

We present ESGBench, a benchmark dataset and evaluation framework designed to assess explainable ESG question answering systems using corporate sustainability reports. The benchmark consists of domain-grounded questions across multiple ESG themes, paired with human-curated answers and supporting evidence to enable fine-grained evaluation of model reasoning. We analyze the performance of state-of-the-art LLMs on ESGBench, highlighting key challenges in factual consistency, traceability, and domain alignment. ESGBench aims to accelerate research in transparent and accountable ESG-focused AI systems.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2511.16438>)

[PDF](<https://arxiv.org/pdf/2511.16438.pdf>)