2026
EACL
EACL 2026
CLARIESG: An End-to-End System for ESG Analysis over Complex Tables in Corporate Reports
Abstract
AbstractSustainability reports contain rich Environmental, Social and Governance (ESG) information, but their heterogeneous layouts and complex multi-table structures pose major challenges for LLMs, especially for unit normalization, cross-document reasoning, and precise numerical computation. We present CLARIESG, an end-to-end system that couples robust table extraction with a structured prompting framework for multi-table filtering, normalization, and program-of-thought reasoning. On ESG-focused multi-table benchmarks, CLARIESG consistently outperforms standard prompting and provides transparent, auditable reasoning, supporting more reliable ESG analysis and greenwashing detection in real-world settings.
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Interdisciplinary Bridge
— Artificial Intelligence and Natural Language Processing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio