{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T19:15:26Z","timestamp":1783106126240,"version":"3.54.6"},"publisher-location":"Singapore","reference-count":27,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819533459","type":"print"},{"value":"9789819533466","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,11,23]],"date-time":"2025-11-23T00:00:00Z","timestamp":1763856000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,23]],"date-time":"2025-11-23T00:00:00Z","timestamp":1763856000000},"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\/978-981-95-3346-6_12","type":"book-chapter","created":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T05:49:59Z","timestamp":1763790599000},"page":"155-167","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Visual Sketchbook: Enhancing Chart-to-Code Generation via\u00a0Reflective Refinement"],"prefix":"10.1007","author":[{"given":"Junzhe","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiheng","family":"Xi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dingwei","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shihan","family":"Dou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Gui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,11,23]]},"reference":[{"key":"12_CR1","unstructured":"Bai, J., et al.: QWEN-VL: a frontier large vision-language model with versatile abilities. arXiv preprint arXiv:2308.12966 (2023)"},{"key":"12_CR2","doi-asserted-by":"publisher","first-page":"1105","DOI":"10.1109\/TVCG.2024.3456155","volume":"31","author":"A Bendeck","year":"2024","unstructured":"Bendeck, A., Stasko, J.: An empirical evaluation of the GPT-4 multimodal language model on visualization literacy tasks. IEEE Trans. Vis. Comput. Graph. 31, 1105\u20131115 (2024)","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"12_CR3","unstructured":"Chen, X., Lin, M., Sch\u00e4rli, N., Zhou, D.: Teaching large language models to self-debug. arXiv preprint arXiv:2304.05128 (2023)"},{"key":"12_CR4","doi-asserted-by":"publisher","unstructured":"Fakhoury, S., Naik, A., Sakkas, G., Chakraborty, S., Musuvathi, M., Lahiri, S.: Exploring the effectiveness of LLM based test-driven interactive code generation: User study and empirical evaluation. In: Proceedings of the 2024 IEEE\/ACM 46th International Conference on Software Engineering: Companion Proceedings, pp. 390\u2013391. ICSE-Companion 2024, Association for Computing Machinery, New York, NY, USA (2024). https:\/\/doi.org\/10.1145\/3639478.3643525","DOI":"10.1145\/3639478.3643525"},{"key":"12_CR5","doi-asserted-by":"publisher","unstructured":"Goswami, K., Mathur, P., Rossi, R., Dernoncourt, F.: PlotGen: multi-agent LLM-based scientific data visualization via multimodal retrieval feedback. In: Companion Proceedings of the ACM on Web Conference 2025, pp. 1672\u20131676. WWW 2025, Association for Computing Machinery, New York, NY, USA (2025).https:\/\/doi.org\/10.1145\/3701716.3716888","DOI":"10.1145\/3701716.3716888"},{"key":"12_CR6","unstructured":"Han, Y., et al.: ChartLLAMA: a multimodal LLM for chart understanding and generation. arXiv preprint arXiv:2311.16483 (2023)"},{"key":"12_CR7","doi-asserted-by":"crossref","unstructured":"He, W., et al.: Distill visual chart reasoning ability from LLMS to MLLMS. arXiv preprint arXiv:2410.18798 (2024)","DOI":"10.18653\/v1\/2025.findings-emnlp.172"},{"key":"12_CR8","unstructured":"Hurst, A., et\u00a0al.: GPT-4O system card. arXiv preprint arXiv:2410.21276 (2024)"},{"key":"12_CR9","unstructured":"Jiang, J., Wang, F., Shen, J., Kim, S., Kim, S.: A survey on large language models for code generation. arXiv preprint arXiv:2406.00515 (2024)"},{"key":"12_CR10","doi-asserted-by":"crossref","unstructured":"Kantharaj, S., et al.: Chart-to-text: a large-scale benchmark for chart summarization. arXiv preprint arXiv:2203.06486 (2022)","DOI":"10.18653\/v1\/2022.acl-long.277"},{"key":"12_CR11","doi-asserted-by":"crossref","unstructured":"Liu, H., Li, C., Wu, Q., Lee, Y.J.: Visual instruction tuning. In: Advances in Neural Information Processing Systems, vol. 36 (2024)","DOI":"10.52202\/075280-1516"},{"key":"12_CR12","unstructured":"Lu, H., et\u00a0al.: DeepSeek-VL: towards real-world vision-language understanding. arXiv preprint arXiv:2403.05525 (2024)"},{"key":"12_CR13","doi-asserted-by":"crossref","unstructured":"Masry, A., Long, D.X., Tan, J.Q., Joty, S., Hoque, E.: ChartQA: a benchmark for question answering about charts with visual and logical reasoning. arXiv preprint arXiv:2203.10244 (2022)","DOI":"10.18653\/v1\/2022.findings-acl.177"},{"key":"12_CR14","unstructured":"Olausson, T.X., Inala, J.P., Wang, C., Gao, J., Solar-Lezama, A.: Is self-repair a silver bullet for code generation? (2024). https:\/\/arxiv.org\/abs\/2306.09896"},{"key":"12_CR15","unstructured":"OpenAI: GPT-4O mini (2024). https:\/\/openai.com\/index\/gpt-4o-mini-advancing-cost-efficient-intelligence\/"},{"key":"12_CR16","unstructured":"OpenAI: GPT-4V (2024). https:\/\/api.semanticscholar.org\/CorpusID:263218031"},{"key":"12_CR17","unstructured":"Quoc, T.T., Minh, D.H., Thanh, T.Q., Nguyen-Duc, A.: An empirical study on self-correcting large language models for data science code generation (2024). https:\/\/arxiv.org\/abs\/2408.15658"},{"key":"12_CR18","unstructured":"Saunders, W., et al.: Self-critiquing models for assisting human evaluators. arXiv preprint arXiv:2206.05802 (2022)"},{"key":"12_CR19","unstructured":"Shi, C., et al.: ChartMimic: evaluating LMM\u2019s cross-modal reasoning capability via chart-to-code generation. arXiv preprint arXiv:2406.09961 (2024)"},{"key":"12_CR20","unstructured":"Team, G., et\u00a0al.: Gemini: a family of highly capable multimodal models. arXiv preprint arXiv:2312.11805 (2023)"},{"key":"12_CR21","doi-asserted-by":"crossref","unstructured":"Wang, H., et al.: Intervenor: prompting the coding ability of large language models with the interactive chain of repair (2024). https:\/\/arxiv.org\/abs\/2311.09868","DOI":"10.18653\/v1\/2024.findings-acl.124"},{"key":"12_CR22","doi-asserted-by":"publisher","unstructured":"Wei, Y., Xia, C.S., Zhang, L.: Copiloting the copilots: fusing large language models with completion engines for automated program repair. In: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pp. 172\u2013184. ESEC\/FSE 2023, ACM (2023). https:\/\/doi.org\/10.1145\/3611643.3616271","DOI":"10.1145\/3611643.3616271"},{"key":"12_CR23","doi-asserted-by":"crossref","unstructured":"Wu, C., et al.: Plot2code: a comprehensive benchmark for evaluating multi-modal large language models in code generation from scientific plots. arXiv preprint arXiv:2405.07990 (2024)","DOI":"10.18653\/v1\/2025.findings-naacl.164"},{"key":"12_CR24","unstructured":"Xi, Z., et\u00a0al.: Enhancing LLM reasoning via critique models with test-time and training-time supervision. arXiv preprint arXiv:2411.16579 (2024)"},{"key":"12_CR25","doi-asserted-by":"crossref","unstructured":"Yang, Z., et\u00a0al.: MatplotAgent: method and evaluation for LLM-based agentic scientific data visualization. arXiv preprint arXiv:2402.11453 (2024)","DOI":"10.18653\/v1\/2024.findings-acl.701"},{"key":"12_CR26","unstructured":"Zhao, X., et al.: ChartCoder: advancing multimodal large language model for chart-to-code generation (2025). https:\/\/arxiv.org\/abs\/2501.06598"},{"key":"12_CR27","unstructured":"Zhipu: GLM-4V-flash (2024). https:\/\/www.bigmodel.cn\/dev\/activities\/free\/glm-4v-flash"}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Chinese Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-3346-6_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T18:17:04Z","timestamp":1783102624000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-3346-6_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,23]]},"ISBN":["9789819533459","9789819533466"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-3346-6_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,23]]},"assertion":[{"value":"23 November 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLPCC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"CCF International Conference on Natural Language Processing and Chinese Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Urumqi","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nlpcc2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/tcci.ccf.org.cn\/conference\/2025\/index.php","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}