{"ID":2878687,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.19295","arxiv_id":"2508.19295","title":"Large VLM-based Stylized Sports Captioning","abstract":"The advent of large (visual) language models (LLM / LVLM) have led to a deluge of automated human-like systems in several domains including social media content generation, search and recommendation, healthcare prognosis, AI assistants for cognitive tasks etc. Although these systems have been successfully integrated in production; very little focus has been placed on sports, particularly accurate identification and natural language description of the game play. Most existing LLM/LVLMs can explain generic sports activities, but lack sufficient domain-centric sports' jargon to create natural (human-like) descriptions. This work highlights the limitations of existing SoTA LLM/LVLMs for generating production-grade sports captions from images in a desired stylized format, and proposes a two-level fine-tuned LVLM pipeline to address that. The proposed pipeline yields an improvement \u003e 8-10% in the F1, and \u003e 2-10% in BERT score compared to alternative approaches. In addition, it has a small runtime memory footprint and fast execution time. During Super Bowl LIX the pipeline proved its practical application for live professional sports journalism; generating highly accurate and stylized captions at the rate of 6 images per 3-5 seconds for over 1000 images during the game play.","short_abstract":"The advent of large (visual) language models (LLM / LVLM) have led to a deluge of automated human-like systems in several domains including social media content generation, search and recommendation, healthcare prognosis, AI assistants for cognitive tasks etc. Although these systems have been successfully integrated in...","url_abs":"https://arxiv.org/abs/2508.19295","url_pdf":"https://arxiv.org/pdf/2508.19295v1","authors":"[\"Sauptik Dhar\",\"Nicholas Buoncristiani\",\"Joe Anakata\",\"Haoyu Zhang\",\"Michelle Munson\"]","published":"2025-08-25T17:50:51Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.LG\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}