@inproceedings{santacroce-etal-2026-clariesg,
    title = "{CLARIESG}: An End-to-End System for {ESG} Analysis over Complex Tables in Corporate Reports",
    author = "Santacroce, Marta  and
      Contalbo, Michele Luca  and
      Pederzoli, Sara  and
      Benassi, Riccardo  and
      Valeria, Venturelli  and
      Paganelli, Matteo  and
      Guerra, Francesco",
    editor = "Croce, Danilo  and
      Leidner, Jochen  and
      Moosavi, Nafise Sadat",
    booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 3: System Demonstrations)",
    month = mar,
    year = "2026",
    address = "Rabat, Marocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-eacl/2026.eacl-demo.7/",
    pages = "86--100",
    ISBN = "979-8-89176-382-1",
    abstract = "Sustainability 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."
}