{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T00:15:31Z","timestamp":1758672931452,"version":"3.44.0"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:p>Video advertising has become a popular marketing strategy on e-commerce platforms, requiring high-level semantic reasoning like selling point discovery, narrative organization. Previous rule-based methods struggle with these complex tasks, and learning-based approaches demand large datasets and high training costs. Recently, Large Language Models have opened incredible opportunities for advancing intelligent video advertisement editing. However, Input-output (IO) prompting and Chain-of-Thought (CoT) struggle to adapt to the nonlinear thinking hierarchy of video editing, where editors iteratively select shots or revert them to explore potential editing solutions. While Tree-of-Thought (ToT) offers a conceptual structure that mirrors this hierarchy, it falls short in aligning with effective video advertising strategies and lacks robust fact-checking mechanisms. To address these, we propose a novel framework, Tree-of-AdEditor (ToAE), which constructs a reasoning tree to mimic human editors, and incorporates domain-specific theories and heuristic fact-checking to identify optimal editing solutions. Specifically, motivated by effective advertisement principles, we develop a \"local-global\" mechanism to guide LLM in both the shot level and sequence level decision-making. We introduce a visual incoherence pruning module to provide external heuristic fact-checking, ensuring visual attractiveness and reducing computation costs. Quantitative experiments and expert evaluation demonstrate the superiority of our method compared to baselines.<\/jats:p>","DOI":"10.24963\/ijcai.2025\/968","type":"proceedings-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T08:10:40Z","timestamp":1758269440000},"page":"8705-8713","source":"Crossref","is-referenced-by-count":0,"title":["Tree-of-AdEditor:  Heuristic Tree Reasoning for Automated Video Advertisement Editing with Large Language Model"],"prefix":"10.24963","author":[{"given":"Yuqi","family":"Zhang","sequence":"first","affiliation":[{"name":"Northwestern Polytechnical University"},{"name":"The Hong Kong Polytechnic University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Guo","sequence":"additional","affiliation":[{"name":"Northwestern Polytechnical University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nuo","family":"Li","sequence":"additional","affiliation":[{"name":"Fudan University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Zhang","sequence":"additional","affiliation":[{"name":"Northwestern Polytechnical University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shijie","family":"Wang","sequence":"additional","affiliation":[{"name":"The Hong Kong Polytechnic University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiwen","family":"Yu","sequence":"additional","affiliation":[{"name":"Northwestern Polytechnical University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qing","family":"Li","sequence":"additional","affiliation":[{"name":"The Hong Kong Polytechnic University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"34","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2025","name":"Thirty-Fourth International Joint Conference on Artificial Intelligence {IJCAI-25}","start":{"date-parts":[[2025,8,16]]},"theme":"Artificial Intelligence","location":"Montreal, Canada","end":{"date-parts":[[2025,8,22]]}},"container-title":["Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T11:35:40Z","timestamp":1758627340000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2025\/968"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2025\/968","relation":{},"subject":[],"published":{"date-parts":[[2025,9]]}}}