AgenticGen: Reward-Guided Agentic Video Generation for Advertising
AgenticGen applies DPO and GRPO reward-guided reasoning to ad video generation, improving TikTok CTR 2.72%, CVR 2.63%, and Advv 9.61%.
AgenticGen decomposes advertising video generation into two trainable reasoning stages, strategy selection and draft generation, supervised by online business feedback. It learns a performance-based reward from accumulated online feedback plus a rubric-based reward aligned with human quality standards, then optimizes policies with DPO followed by GRPO using process and outcome rewards. Online A/B experiments in the TikTok advertising system show CTR up 2.72%, CVR up 2.63%, and Advv up 9.61% over an SFT baseline.
- Decomposes ad generation into trainable strategy-selection and draft-generation stages supervised by business feedback.
- Learns performance-based reward from online feedback plus rubric-based reward aligned with human quality standards.
- DPO shifts policies toward online preferences; GRPO refines with process and outcome rewards.
- Online A/B tests show CTR +2.72%, CVR +2.63%, Advv +9.61% over SFT baseline.
- Vendors
- TikTok
- Products
- AgenticGen
- Organizations
- TikTok
From the original article
1 min read at huggingface.co
Advertising video generation is not only a video synthesis task, but also a product-conditioned reasoning problem whose success is measured by online business metrics.
By Xingyuan Bu, Chengru Song, Hao Zhou · huggingface.co
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