{"ID":2858043,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.07993","arxiv_id":"2510.07993","title":"Leveraging Author-Specific Context for Scientific Figure Caption Generation: 3rd SciCap Challenge","abstract":"Scientific figure captions require both accuracy and stylistic consistency to convey visual information. Here, we present a domain-specific caption generation system for the 3rd SciCap Challenge that integrates figure-related textual context with author-specific writing styles using the LaMP-Cap dataset. Our approach uses a two-stage pipeline: Stage 1 combines context filtering, category-specific prompt optimization via DSPy's MIPROv2 and SIMBA, and caption candidate selection; Stage 2 applies few-shot prompting with profile figures for stylistic refinement. Our experiments demonstrate that category-specific prompts outperform both zero-shot and general optimized approaches, improving ROUGE-1 recall by +8.3\\% while limiting precision loss to -2.8\\% and BLEU-4 reduction to -10.9\\%. Profile-informed stylistic refinement yields 40--48\\% gains in BLEU scores and 25--27\\% in ROUGE. Overall, our system demonstrates that combining contextual understanding with author-specific stylistic adaptation can generate captions that are both scientifically accurate and stylistically faithful to the source paper.","short_abstract":"Scientific figure captions require both accuracy and stylistic consistency to convey visual information. Here, we present a domain-specific caption generation system for the 3rd SciCap Challenge that integrates figure-related textual context with author-specific writing styles using the LaMP-Cap dataset. Our approach u...","url_abs":"https://arxiv.org/abs/2510.07993","url_pdf":"https://arxiv.org/pdf/2510.07993v1","authors":"[\"Watcharapong Timklaypachara\",\"Monrada Chiewhawan\",\"Nopporn Lekuthai\",\"Titipat Achakulvisut\"]","published":"2025-10-09T09:30:28Z","proceeding":"cs.CL","tasks":"[\"cs.CL\",\"cs.AI\"]","methods":"[]","has_code":false}