{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T01:05:53Z","timestamp":1780362353281,"version":"3.54.1"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031984587","type":"print"},{"value":"9783031984594","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\/978-3-031-98459-4_24","type":"book-chapter","created":{"date-parts":[[2025,7,19]],"date-time":"2025-07-19T19:29:16Z","timestamp":1752953356000},"page":"336-349","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["From Text to\u00a0Visuals: Using LLMs to\u00a0Generate Math Diagrams with\u00a0Vector Graphics"],"prefix":"10.1007","author":[{"given":"Jaewook","family":"Lee","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeongah","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wanyong","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Lan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,20]]},"reference":[{"key":"24_CR1","doi-asserted-by":"crossref","unstructured":"Antol, S., Agrawal, A., Lu, J., Mitchell, M., Batra, D., Zitnick, C.L., Parikh, D.: VQA: visual question answering. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2425\u20132433 (2015)","DOI":"10.1109\/ICCV.2015.279"},{"issue":"3","key":"24_CR2","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1023\/A:1024312321077","volume":"52","author":"A Arcavi","year":"2003","unstructured":"Arcavi, A.: The role of visual representations in the learning of mathematics. Educ. Stud. Math. 52(3), 215\u2013241 (2003)","journal-title":"Educ. Stud. Math."},{"key":"24_CR3","unstructured":"Belouadi, J., Lauscher, A., Eger, S.: AutomaTikZ: text-guided synthesis of scientific vector graphics with TikZ. arXiv preprint arXiv:2310.00367 (2023)"},{"key":"24_CR4","unstructured":"Bray, T., Paoli, J., Sperberg-McQueen, C.M., Maler, E., Yergeau, F.: Extensible Markup Language (XML) 1.0 (Fifth Edition). W3C (2008). https:\/\/www.w3.org\/TR\/xml\/"},{"key":"24_CR5","unstructured":"Cai, M., Huang, Z., Li, Y., Ojha, U., Wang, H., Lee, Y.J.: Leveraging large language models for scalable vector graphics-driven image understanding. arXiv preprint arXiv:2306.06094 (2023)"},{"key":"24_CR6","doi-asserted-by":"crossref","unstructured":"Cai, S., Bao, K., Guo, H., Zhang, J., Song, J., Zheng, B.: GeoGPT4V: towards geometric multi-modal large language models with geometric image generation. arXiv preprint arXiv:2406.11503 (2024)","DOI":"10.18653\/v1\/2024.emnlp-main.44"},{"key":"24_CR7","doi-asserted-by":"crossref","unstructured":"Dong, Q., et al.: A survey on in-context learning. In: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pp. 1107\u20131128. Association for Computational Linguistics (2024)","DOI":"10.18653\/v1\/2024.emnlp-main.64"},{"key":"24_CR8","doi-asserted-by":"crossref","unstructured":"Feng, W., et al.: Exploring automated distractor generation for math multiple-choice questions via large language models. In: Findings of the Association for Computational Linguistics: NAACL 2024, pp. 3067\u20133082 (2024)","DOI":"10.18653\/v1\/2024.findings-naacl.193"},{"key":"24_CR9","doi-asserted-by":"crossref","unstructured":"Fernandez, N., Scarlatos, A., Feng, W., Woodhead, S., Lan, A.: DiVERT: distractor generation with variational errors represented as text for math multiple-choice questions. arXiv preprint arXiv:2406.19356 (2024)","DOI":"10.18653\/v1\/2024.emnlp-main.512"},{"key":"24_CR10","unstructured":"Ferraiolo, J., Jun, F., Jackson, D.: Scalable vector graphics (SVG) 1.0 specification. iUniverse Bloomington (2000)"},{"key":"24_CR11","unstructured":"Gao, J., et\u00a0al.: G-LLaVA: solving geometric problem with multi-modal large language model. arXiv preprint arXiv:2312.11370 (2023)"},{"key":"24_CR12","doi-asserted-by":"crossref","unstructured":"Huang, Z., Wu, T., Lin, W., Zhang, S., Chen, J., Wu, F.: AutoGeo: automating geometric image dataset creation for enhanced geometry understanding. arXiv preprint arXiv:2409.09039 (2024)","DOI":"10.1109\/TMM.2025.3557720"},{"key":"24_CR13","unstructured":"IXL Learning: IXL learning (2025). https:\/\/www.ixl.com. Accessed 15 Feb 2025"},{"key":"24_CR14","doi-asserted-by":"crossref","unstructured":"Khan Academy: Khan academy. https:\/\/www.khanacademy.org. Accessed 23 Jan 2025","DOI":"10.5465\/AMPROC.2025.464bp"},{"key":"24_CR15","unstructured":"Khan Academy: supercharge your teaching experience with khanmigo (2023). https:\/\/www.khanmigo.ai\/"},{"key":"24_CR16","doi-asserted-by":"publisher","unstructured":"Lee, J., Smith, D., Woodhead, S., Lan, A.: Math multiple choice question generation via human-large language model collaboration. In: PaaBen, B., Epp, C.D. (eds.) Proceedings of the 17th International Conference on Educational Data Mining, pp. 941\u2013946. International Educational Data Mining Society, Atlanta, Georgia, USA (2024). https:\/\/doi.org\/10.5281\/zenodo.12730005","DOI":"10.5281\/zenodo.12730005"},{"key":"24_CR17","doi-asserted-by":"publisher","unstructured":"Mayer, R.E., Fiorella, L., Stull, A., Boone, A.P., Keppens, K.: Learning with visualizations helps: a meta-analysis of visualization interventions in mathematics education. Thinking Skills Creativity 49, 101380 (2024). https:\/\/doi.org\/10.1016\/j.tsc.2024.101380, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1747938X24000484","DOI":"10.1016\/j.tsc.2024.101380"},{"key":"24_CR18","unstructured":"Mitra, A., Khanpour, H., Rosset, C., Awadallah, A.: Orca-Math: unlocking the potential of SLMs in grade school math. arXiv preprint arXiv:2402.14830 (2024)"},{"key":"24_CR19","unstructured":"Nishina, K., Matsui, Y.: SVGEditBench: a benchmark dataset for quantitative assessment of LLM\u2019s SVG editing capabilities. arXiv preprint arXiv:2404.13710 (2024)"},{"key":"24_CR20","unstructured":"OpenAI: Dall$$\\cdot $$e 3 (2023). https:\/\/openai.com\/dall-e. Accessed Feb 2025"},{"key":"24_CR21","unstructured":"OpenAI: Hello GPT-4O (2024). https:\/\/openai.com\/index\/hello-gpt-4o\/. Accessed 19 Feb 2025"},{"key":"24_CR22","doi-asserted-by":"crossref","unstructured":"Presmeg, N.: Visualization and learning in mathematics education. Encyclopedia Math. Educ., 900\u2013904 (2020)","DOI":"10.1007\/978-3-030-15789-0_161"},{"key":"24_CR23","doi-asserted-by":"publisher","unstructured":"Scarlatos, A., Smith, D., Woodhead, S., Lan, A.: Improving the validity of automatically generated feedback via reinforcement learning. In: Olney, A.M., Chounta, IA., Liu, Z., Santos, O.C., Bittencourt, I.I. (eds) International Conference on Artificial Intelligence in Education, pp. 280\u2013294. Springer, Cham (2024). https:\/\/doi.org\/10.1007\/978-3-031-64302-6_20","DOI":"10.1007\/978-3-031-64302-6_20"},{"key":"24_CR24","doi-asserted-by":"crossref","unstructured":"Shridhar, K., Macina, J., El-Assady, M., Sinha, T., Kapur, M., Sachan, M.: Automatic generation of socratic subquestions for teaching math word problems. In: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pp. 4136\u20134149 (2022)","DOI":"10.18653\/v1\/2022.emnlp-main.277"},{"issue":"3","key":"24_CR25","doi-asserted-by":"publisher","first-page":"322","DOI":"10.1016\/j.learninstruc.2007.02.006","volume":"17","author":"Y Uesaka","year":"2007","unstructured":"Uesaka, Y., Manalo, E., Ichikawa, S.: What kinds of perceptions and daily learning behaviors promote students\u2019 use of diagrams in mathematics problem solving? Learn. Instr. 17(3), 322\u2013335 (2007)","journal-title":"Learn. Instr."},{"key":"24_CR26","doi-asserted-by":"publisher","unstructured":"Uesaka, Y., Manalo, E., Ichikawa, S.: The effects of perception of efficacy and diagram construction skills on students\u2019 spontaneous use of diagrams when solving math word problems. In: Goel, A.K., Jamnik, M., Narayanan, N.H. (eds) Diagrammatic Representation and Inference: 6th International Conference, Diagrams 2010, Portland, OR, USA, August 9-11, 2010. Proceedings, pp. 197\u2013211. Springer, Cham (2010). https:\/\/doi.org\/10.1007\/978-3-642-14600-8_19","DOI":"10.1007\/978-3-642-14600-8_19"},{"key":"24_CR27","doi-asserted-by":"crossref","unstructured":"Ye, K., et al.: Penrose: from mathematical notation to beautiful diagrams. ACM Trans. Graph. (TOG) 39(4), 144:1\u2013144:16 (2020)","DOI":"10.1145\/3386569.3392375"},{"key":"24_CR28","unstructured":"Zhang, R., et al.: MAVIS: mathematical visual instruction tuning. arXiv preprint arXiv:2407.08739 (2024)"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence in Education"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-98459-4_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T00:27:45Z","timestamp":1780360065000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-98459-4_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031984587","9783031984594"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-98459-4_24","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":"20 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIED","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Intelligence in Education","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Palermo","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":"22 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aied2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aied2025.itd.cnr.it\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}