{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,5]],"date-time":"2025-04-05T12:10:06Z","timestamp":1743855006863,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031887130","type":"print"},{"value":"9783031887147","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-88714-7_12","type":"book-chapter","created":{"date-parts":[[2025,4,5]],"date-time":"2025-04-05T11:40:41Z","timestamp":1743853241000},"page":"148-155","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Improving Language Model Performance by\u00a0Training on\u00a0Prototypical Contradictions"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9610-6026","authenticated-orcid":false,"given":"Maren","family":"Pielka","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marie-Christin","family":"Freischlad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Svetlana","family":"Schmidt","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6680-8210","authenticated-orcid":false,"given":"Rafet","family":"Sifa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,4,4]]},"reference":[{"key":"12_CR1","unstructured":"Abdin, M., et al.: Phi-3 technical report: a highly capable language model locally on your phone (2024). https:\/\/arxiv.org\/abs\/2404.14219"},{"key":"12_CR2","unstructured":"Anil, R., et\u00a0al.: Gemini: a family of highly capable multimodal models (2024). https:\/\/arxiv.org\/abs\/2312.11805"},{"key":"12_CR3","doi-asserted-by":"crossref","unstructured":"Bowman, S., Angeli, G., Potts, C., Manning, C.: A large annotated corpus for learning natural language inference. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (2015). https:\/\/aclanthology.org\/D15-1075","DOI":"10.18653\/v1\/D15-1075"},{"key":"12_CR4","doi-asserted-by":"crossref","unstructured":"Conneau, A., et al.: Unsupervised cross-lingual representation learning at scale. In: Annual Meeting of the Association for Computational Linguistics (2019). https:\/\/api.semanticscholar.org\/CorpusID:207880568","DOI":"10.18653\/v1\/2020.acl-main.747"},{"key":"12_CR5","doi-asserted-by":"crossref","unstructured":"Deu\u00dfer, T., et al.: Contradiction detection in financial reports. In: Proceedings of the Northern Lights Deep Learning Workshop, vol.\u00a04 (2023)","DOI":"10.7557\/18.6799"},{"key":"12_CR6","unstructured":"Jiang, A.Q., et al.: Mixtral of experts (2024). https:\/\/arxiv.org\/abs\/2401.04088"},{"key":"12_CR7","unstructured":"de\u00a0Marneffe, M.C., Rafferty, A., Manning, C.: Finding Contradictions in Text. In: Proceedings of ACL-08: HLT. ACL (2008). https:\/\/aclanthology.org\/P08-1118"},{"key":"12_CR8","unstructured":"Martin, L., et\u00a0al.: Llama 2: Open foundation and fine-tuned chat models (2023)"},{"key":"12_CR9","doi-asserted-by":"crossref","unstructured":"Moreno-Sandoval, A., Porta-Zamorano, J., Carbajo-Coronado, B., Samy, D., Mariko, D., El-Haj, M.: The financial document causality detection shared task (fincausal 2023). In: 4th Joint Workshop on Financial Narrative Processing @BigData2023 (2023)","DOI":"10.1109\/BigData59044.2023.10386745"},{"key":"12_CR10","unstructured":"OpenAI: Gpt-4 technical report. arXiv:2303.08774 (2023)"},{"key":"12_CR11","doi-asserted-by":"crossref","unstructured":"Pielka, M., Rode, F., Pucknat, L., Deu\u00dfer, T., Sifa, R.: A linguistic investigation of machine learning based contradiction detection models: An empirical analysis and future perspectives. In: Proceedings of ICMLA 2022 (2022)","DOI":"10.1109\/ICMLA55696.2022.00253"},{"key":"12_CR12","doi-asserted-by":"crossref","unstructured":"Pielka, M., Schmidt, S., Sifa, R.: Generating prototypes for contradiction detection using large language models and linguistic rules. In: Proceedings of the IEEE International Conference on Big Data (2023)","DOI":"10.1109\/BigData59044.2023.10386499"},{"key":"12_CR13","doi-asserted-by":"crossref","unstructured":"Pielka, M., Sifa, R.: Insights about causalities in financial text - towards an informed approach. In: IEEE Big Data Conference (2024)","DOI":"10.1109\/BigData62323.2024.10825863"},{"key":"12_CR14","unstructured":"Pucknat, L., Pielka, M., Sifa, R.: Towards informed pre-training for critical error detection in English-German. In: Lernen. Wissen. Daten. Analysen. (LWDA) (2022)"},{"key":"12_CR15","unstructured":"Radford, A., Narasimhan, K.: Improving language understanding by generative pre-training (2018). https:\/\/api.semanticscholar.org\/CorpusID:49313245"},{"key":"12_CR16","unstructured":"Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I.: Language models are unsupervised multitask learners (2019). https:\/\/api.semanticscholar.org\/CorpusID:160025533"},{"key":"12_CR17","unstructured":"von Rueden, L., Houben, S., Cvejoski, K., Bauckhage, C., Piatkowski, N.: Informed pre-training on prior knowledge. In: Proceedings of the International Joint Conference on Neural Networks (2022). https:\/\/api.semanticscholar.org\/CorpusID:248986128"},{"key":"12_CR18","unstructured":"Specia, L., et al.: Findings of the WMT 2021 shared task on quality estimation. In: Sixth Conference on Machine Translation (WMT) (2021)"},{"key":"12_CR19","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Proceedings of the 31st International Conference on Neural Information Processing Systems (2017)"}],"container-title":["Lecture Notes in Computer Science","Advances in Information Retrieval"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-88714-7_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,5]],"date-time":"2025-04-05T11:41:09Z","timestamp":1743853269000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-88714-7_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031887130","9783031887147"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-88714-7_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"4 April 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECIR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Information Retrieval","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lucca","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 April 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 April 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"47","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecir2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ecir2025.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}