ZORA Publication List

Publications

• 2026

  • Spacey Martín, R., Ranger, N., Schimanski, T., & Leippold, M. (2026). Empirically assessing corporate adaptation and resilience disclosure using AI Npj Climate Action, 5, 22. https://doi.org/10.1038/s44168-025-00321-7

• 2025

  • Colesanti Senni, C., Vaghefi, A. S., Manekar, T., Schimanski, T., & Leippold, M. (2025). Using AI to assess the decision-usefulness of corporates’ nature-related disclosures Environmental Research Communications, 7, 115006. https://doi.org/10.1088/2515-7620/ae1357
  • Ni, J., Schimanski, T., Lin, M., Sachan, M., Ash, E., & Leippold, M. (2025). DIRAS: Efficient LLM Annotation of Document Relevance for Retrieval Augmented Generation (L. Chiruzzo, A. Ritter, & L. Wang, Eds.; Volume 1: Long Papers; Issue Volume 1: Long Papers, pp. 5238–5258). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.naacl-long.271
  • Leippold, M., Vaghefi, S. A., Stammbach, D., Muccione, V., Bingler, J., Ni, J., Colesanti Senni, C., Wekhof, T., Schimanski, T., Gostlow, G., Yu, T., Luterbacher, J., & Huggel, C. (2025). Automated fact-checking of climate claims with large language models Npj Climate Action, 4, 17. https://doi.org/10.1038/s44168-025-00215-8
  • Colesanti Senni, C., Schimanski, T., Bingler, J., Ni, J., & Leippold, M. (2025). Using AI to assess corporate climate transition disclosures Environmental Research, 7, 021010. https://doi.org/10.1088/2515-7620/ad9e88

• 2024

  • Schimanski, T., Ni, J., Martín, R. S., Ranger, N., & Leippold, M. (2024). ClimRetrieve: A Benchmarking Dataset for Information Retrieval from Corporate Climate Disclosures Proceedings of the Conference on Empirical Methods in Natural Language Processing, 17509–17524. https://doi.org/10.18653/v1/2024.emnlp-main.969
  • Schimanski, T., Ni, J., Kraus, M., Ash, E., & Leippold, M. (2024). Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering Proceedings of the Annual Meeting of the Association for Computational Linguistics, 1913–1931. https://doi.org/10.18653/v1/2024.acl-long.105
  • Muccione, V., Vaghefi, S. A., Bingler, J., Allen, S. K., Kraus, M., Gostlow, G., Wekhof, T., Colesanti-Senni, C., Stammbach, D., Ni, J., Schimanski, T., Yu, T., Wang, Q., Huggel, C., Luterbacher, J., Biesbroek, R., & Leippold, M. (2024). Integrating artificial intelligence with expert knowledge in global environmental assessments: opportunities, challenges and the way ahead Regional Environmental Change, 24, 121. https://doi.org/10.1007/s10113-024-02283-8
  • Adams, J. S., Altantzis, C., Beucler, T., Bingler, J., Brown, S., Brunschwiler, T., Colesanti-Senni, C., Muccione, V., Roeoesli, C., Schimanski, T., Vaghefi, S. A., Wegner, J. D., & et al. (2024). How to use the power of AI to reduce the impact of climate change on Switzerland Swiss Academy of Engineering Sciences, SATW. https://www.satw.ch/de/publikationen/wie-sich-das-potenzial-von-ki-nutzen-laesst-um-die-auswirkungen-des-klimawandels-auf-die-schweiz-zu-reduzieren
  • Schimanski, T., Reding, A., Reding, N., Bingler, J., Kraus, M., & Leippold, M. (2024). Bridging the gap in ESG measurement: Using NLP to quantify environmental, social, and governance communication Finance Research Letters, 61, 104979. https://doi.org/10.1016/j.frl.2024.104979

• 2023

  • Ni, J., Bingler, J., Colesanti Senni, C., Kraus, M., Gostlow, G., Schimanski, T., Stammbach, D., Ashraf Vaghefi, S., Wang, Q., Webersinke, N., Wekhof, T., Yu, T., & Leippold, M. (2023). CHATREPORT: Democratizing Sustainability Disclosure Analysis through LLM-based Tools Proceedings of the Conference on Empirical Methods in Natural Language Processing, 21–51. https://doi.org/10.18653/v1/2023.emnlp-demo.3
  • Schimanski, T., Bingler, J., Kraus, M., Hyslop, C., & Leippold, M. (2023). ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targets Proceedings of the Conference on Empirical Methods in Natural Language Processing, 15745–15756. https://doi.org/10.18653/v1/2023.emnlp-main.975
  • Vaghefi, S. A., Stammbach, D., Muccione, V., Bingler, J., Ni, J., Kraus, M., Allen, S., Colesanti-Senni, C., Wekhof, T., Schimanski, T., Gostlow, G., Yu, T., Wang, Q., Webersinke, N., Huggel, C., & Leippold, M. (2023). ChatClimate: Grounding conversational AI in climate science Communications Earth & Environment, 4, 480. https://doi.org/10.1038/s43247-023-01084-x