Publications in Computer Science

ZORA Publication List

Publications

• 2025

  • Usmanova, A., Abdullah, R., Banerjee, D., Leippold, M., & Usbeck, R. (2025). ReportGRI: Automating GRI Alignment and Report Assessment 6723–6727. https://doi.org/10.1145/3746252.3761469
  • Xiong, C., Ni, J., Fan, Y., Zouhar, V., Rooein, D., Calvo-Bartolomé, L., Hoyle, A. M., Jin, Z., Sachan, M., Leippold, M., Hovy, D., El-Assady, M., & Ash, E. (2025). Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification (I. Habernal, P. Schulam, & J. Tiedemann, Eds.; pp. 354–364). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.emnlp-demos.25
  • Kolli, I., Vaghefi, S., Colesanti Senni, C., Raj, S., & Leippold, M. (2025). Automated Evidence Extraction and Scoring for Corporate Climate Policy Engagement: A Multilingual RAG Approach (I. Habernal, P. Schulam, & J. Tiedemann, Eds.; pp. 111–129). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.emnlp-demos.9
  • 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

• 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
  • Bulian, J., Schäfer, M. S., Amini, A., Lam, H., Ciaramita, M., Gaiarin, B., Chen Hübscher, M., Buck, C., Mede, N. G., Leippold, M., & Strauß, N. (2024, July 27). Assessing Large Language Models on climate information Proceedings of Machine Learning Research. 41st International Conference on Machine Learning, Vienna. https://doi.org/10.48550/arXiv.2310.02932

• 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
  • Leippold, M., Stammbach, D., Webersinke, N., Bingler, J. A., & Kraus, M. (2023). Environmental Claim Detection Proceedings of the Annual Meeting of the Association for Computational Linguistics, 1051–1066. https://doi.org/10.18653/v1/2023.acl-short.91
  • Leippold, M., Ni, J., Jin, Z., Wang, Q., & Sachan, M. (2023). When does aggregating multiple skills with multi-task learning work? A case study in financial NLP Proceedings of the Annual Meeting of the Association for Computational Linguistics, 7465–7488. https://aclanthology.org/2023.acl-long.412/
  • Leippold, M., Stammbach, D., Webersinke, N., Bingler, J. A., & Kraus, M. (2023). A dataset for detecting real-world environmental claims 1–14. https://doi.org/10.48550/arXiv.2209.00507

• 2022

  • Leippold, M., Hershcovich, D., Bingler, J. A., Kraus, M., & Webersinke, N. (2022). Towards Climate Awareness in NLP Research Proceedings of the Conference on Empirical Methods in Natural Language Processing, 2480–2494. https://doi.org/10.18653/v1/2022.emnlp-main.159
  • Leippold, M., Bingler, J. A., Kraus, M., & Webersinke, N. (2022, November 19). ClimateBert: A pretrained language model for climate-related text AAAI Fall Symposium 2022, Arlington. https://doi.org/10.48550/arXiv.2110.12010

• 2020

  • Mishra, R., Yadav, P., Calizzano, R., & Leippold, M. (2020, December 17). MuSeM: Detecting Incongruent News Headlines using Mutual Attentive Semantic Matching International Conference on Machine Learning and Applications (ICMLA) 2020, Miami.
  • Diggelmann, T., Boyd-Graber, J., Bulian, J., Ciaramita, M., & Leippold, M. (2020, December 11). Climate-fever: A Dataset for Verification of Real-World Climate Claims Tackling Climate Change with Machine Learning workshop at NeurIPS 2020, Online.
  • Varini, F., Boyd-Graber, J., Ciaramita, M., & Leippold, M. (2020, December 11). ClimaText: A Dataset for Climate Change Topic Detection Tackling Climate Change with Machine Learning workshop at NeurIPS 2020, Online.
  • Mishra, R., Gupta, D., & Leippold, M. (2020, November 20). Generating Fact Checking Summaries for Web Claims The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), online.