{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:04:39Z","timestamp":1760241879419,"version":"build-2065373602"},"publisher-location":"Cham","reference-count":10,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031972065","type":"print"},{"value":"9783031972072","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T00:00:00Z","timestamp":1760227200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T00:00:00Z","timestamp":1760227200000},"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":[[2026]]},"DOI":"10.1007\/978-3-031-97207-2_10","type":"book-chapter","created":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:23:11Z","timestamp":1760196191000},"page":"128-135","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluating Locally Run Large Language Models on\u00a0Toxic Meme Analysis"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8431-081X","authenticated-orcid":false,"given":"Erik","family":"Tjong Kim Sang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2392-6300","authenticated-orcid":false,"given":"Delfina S.","family":"Martinez Pandiani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3357-9130","authenticated-orcid":false,"given":"Davide","family":"Ceolin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,10,12]]},"reference":[{"key":"10_CR1","unstructured":"Brown, T.B., et al.: Language models are few-shot learners. In: Proceedings of the 34th International Conference on Neural Information Processing Systems. NIPS \u201920, Curran Associates Inc., Red Hook, NY, USA (2020)"},{"key":"10_CR2","unstructured":"Cui, S., et al.: FFT: Towards harmlessness evaluation and analysis for LLMs with factuality, fairness, toxicity (2024). https:\/\/arxiv.org\/abs\/2311.18580"},{"key":"10_CR3","doi-asserted-by":"publisher","unstructured":"Koh, H., Kim, D., Lee, M., Jung, K.: Can LLMs recognize toxicity? A structured investigation framework and toxicity metric. In: Al-Onaizan, Y., Bansal, M., Chen, Y.N. (eds.) Findings of the Association for Computational Linguistics: EMNLP 2024, pp. 6092\u20136114. Association for Computational Linguistics, Miami, Florida, USA (2024). https:\/\/doi.org\/10.18653\/v1\/2024.findings-emnlp.353, https:\/\/aclanthology.org\/2024.findings-emnlp.353\/","DOI":"10.18653\/v1\/2024.findings-emnlp.353"},{"key":"10_CR4","unstructured":"Liu, H., Li, C., Wu, Q., Lee, Y.J.: Visual instruction tuning. In: Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S. (eds.) Advances in Neural Information Processing Systems. vol.\u00a036, pp. 34892\u201334916. Curran Associates, Inc. (2023). https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2023\/file\/6dcf277ea32ce3288914faf369fe6de0-Paper-Conference.pdf"},{"key":"10_CR5","unstructured":"Martinez\u00a0Pandiani, D., Tjong Kim\u00a0Sang, E., Ceolin, D.: OnToxKG: an ontology-based knowledge graph of toxic symbols and their manifestations. In: 25th International Conference on Web Engineering. Springer (2025)"},{"key":"10_CR6","doi-asserted-by":"crossref","unstructured":"Martinez\u00a0Pandiani, D.S., Tjong Kim\u00a0Sang, E., Ceolin, D.: Toxic memes: A survey of computational perspectives on the detection and explanation of meme toxicities (2024). https:\/\/arxiv.org\/abs\/2406.07353","DOI":"10.1016\/j.osnem.2025.100317"},{"key":"10_CR7","unstructured":"Wang, Y., Li, H., Han, X., Nakov, P., Baldwin, T.: Do-not-answer: evaluating safeguards in LLMs. In: Graham, Y., Purver, M. (eds.) Findings of the Association for Computational Linguistics: EACL 2024, pp. 896\u2013911. Association for Computational Linguistics, St. Julian\u2019s, Malta (2024). https:\/\/aclanthology.org\/2024.findings-eacl.61\/"},{"key":"10_CR8","unstructured":"de\u00a0Wynter, A., et al.: RTP-LX: Can LLMs evaluate toxicity in multilingual scenarios? (2024). https:\/\/arxiv.org\/abs\/2404.14397"},{"key":"10_CR9","unstructured":"Yang, Y., Dan, S., Roth, D., Lee, I.: Benchmarking LLM guardrails in handling multilingual toxicity (2024). https:\/\/arxiv.org\/abs\/2410.22153"},{"key":"10_CR10","doi-asserted-by":"crossref","unstructured":"Zhang, J., Wu, Q., Xu, Y., Cao, C., Du, Z., Psounis, K.: Efficient toxic content detection by bootstrapping and distilling large language models. Proc. AAAI Conf. Artif. Intell. 38(19), 21779\u201321787 (2024)","DOI":"10.1609\/aaai.v38i19.30178"}],"container-title":["Lecture Notes in Computer Science","Web Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-97207-2_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:23:14Z","timestamp":1760196194000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-97207-2_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,12]]},"ISBN":["9783031972065","9783031972072"],"references-count":10,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-97207-2_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,12]]},"assertion":[{"value":"12 October 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICWE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Web Engineering","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Delft","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","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":"30 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icwe2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icwe2025.webengineering.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}