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

November 20, 2025 ยท Declared Dead ยท ๐Ÿ› arXiv.org

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Authors Sherine George, Nithish Saji arXiv ID 2511.16438 Category cs.CL: Computation & Language Cross-listed cs.IR Citations 0 Venue arXiv.org Last Checked 6 months ago
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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