{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T02:27:51Z","timestamp":1773800871666,"version":"3.50.1"},"reference-count":0,"publisher":"Association for the Advancement of Artificial Intelligence (AAAI)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AAAI"],"abstract":"<jats:p>Regulatory compliance checking for online medical advertisements poses a critical public safety challenge distinct from traditional fact-checking, particularly in low-resource languages. Existing automated systems are ill-suited for the authorization-based, evidence-grounded, and explainable reasoning this task demands. To address this gap, we introduce VietCheckMed, a novel retrieval-augmented framework, and VietAestheticAds, the first large-scale, expert-validated benchmark for this task, comprising 8,329 advertisements paired with an authoritative regulatory corpus of 9,978 facilities. Comprehensive experiments demonstrate that our evidence-grounded approach is essential, substantially outperforming powerful unassisted LLM baselines by over 0.3805 F1-score. A detailed analysis reveals that the primary remaining challenges are nuanced failures in semantic and logical reasoning, defining a clear frontier for future research. To promote advances in regulatory technology and responsible AI, our dataset, code, and evaluation scripts will be made publicly available. This work contributes a foundational methodology and a vital public resource for developing responsible AI in high-stakes regulatory domains.<\/jats:p>","DOI":"10.1609\/aaai.v40i2.37077","type":"journal-article","created":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T22:48:03Z","timestamp":1773787683000},"page":"1069-1077","source":"Crossref","is-referenced-by-count":0,"title":["VietCheckMed: Explainable Regulatory Compliance Checking for Medical Advertisements on Vietnamese Social Media"],"prefix":"10.1609","volume":"40","author":[{"given":"Nguyen Thanh","family":"Tam","sequence":"first","affiliation":[]},{"given":"Khanh Quoc","family":"Tran","sequence":"additional","affiliation":[]},{"given":"Dat Thanh","family":"Pham","sequence":"additional","affiliation":[]},{"given":"Truong","family":"Phu Le","sequence":"additional","affiliation":[]},{"given":"Nguyen Hoang Gia","family":"Han","sequence":"additional","affiliation":[]},{"given":"Binh T.","family":"Nguyen","sequence":"additional","affiliation":[]}],"member":"9382","published-online":{"date-parts":[[2026,3,14]]},"container-title":["Proceedings of the AAAI Conference on Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/download\/37077\/41039","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/download\/37077\/41039","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T22:48:03Z","timestamp":1773787683000},"score":1,"resource":{"primary":{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/37077"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,14]]},"references-count":0,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,3,17]]}},"URL":"https:\/\/doi.org\/10.1609\/aaai.v40i2.37077","relation":{},"ISSN":["2374-3468","2159-5399"],"issn-type":[{"value":"2374-3468","type":"electronic"},{"value":"2159-5399","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3,14]]}}}