{"id":"580b3158-17e5-4c09-84c3-d2e5d245a06d","url":"https://api.tumn.com/news/580b3158-17e5-4c09-84c3-d2e5d245a06d","title":"GenRecs Tokenization: Transforming Ads Recommendation at Meta with Stable Model Vocabulary","summary":"Generative Recommenders (GenRecs) represent a paradigm shift from scoring every ad to reasoning about ad content and user preferences together in order to predict the best outcome for advertisers. Leveraging the world knowledge built into LLMs makes ad matching more intelligent a","sections":[],"faq":[],"sources":[{"url":"https://engineering.fb.com/2026/10/19/ml-applications/genrecs-tokenization-transforming-ads-recommendation-at-meta-with-stable-model-vocabulary/","title":"Meta Engineering","publishedAt":"2026-10-19T16:00:47.000Z"}],"author":"TUMN 큐레이션","aiAssisted":false,"reviewStatus":"automated","reviewNote":"원문 제목과 공개된 발췌를 인용하고 원문으로 연결합니다. 내용을 재작성하거나 요약하지 않았습니다.","publishedAt":"2026-10-19T16:00:47.000Z","modifiedAt":"2026-10-19T21:25:34.000Z","checkedAt":"2026-10-19T21:25:34.336Z","language":"ko","kind":"link","sourceLabel":"AI 공식","profile":null,"via":null,"formats":{"json":"https://api.tumn.com/news/580b3158-17e5-4c09-84c3-d2e5d245a06d.json","markdown":"https://api.tumn.com/news/580b3158-17e5-4c09-84c3-d2e5d245a06d.md"}}