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

Sherine George, Nithish Saji
11/20/2025
cs.CLcs.IR

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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.

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Cite this paper

@article{george2025esgbench,
  title  = {ESGBench: A Benchmark for Explainable ESG Question Answering in Corporate Sustainability Reports},
  author = {Sherine George and Nithish Saji},
  year   = {2025},
  eprint = {2511.16438},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2511.16438v1}
}

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