6 papers
Offline-to-Online Creative Optimization with Generative Models and Adaptive Testing
Kevin Lee, Benjamin Letham, Zhiyuan Jerry Lin +5
Ad creative optimization is increasingly constrained by evaluation rather than generation. Generative models can produce many plausible creatives, but reliable evaluation requires…
Decoding the Hook: A Multimodal LLM Framework for Analyzing the Hooking Period of Video Ads
Kunpeng Zhang, Poppy Zhang, Shawndra Hill +1
Video-based ads are a vital medium for brands to engage consumers, with social media platforms leveraging user data to optimize ad delivery and boost engagement. A crucial but unde…
MLLM-VADStory: Domain Knowledge-Driven Multimodal LLMs for Video Ad Storyline Insights
Jasmine Yang, Poppy Zhang, Shawndra Hill
We propose MLLM-VADStory, a novel domain knowledge-guided multimodal large language models (MLLM) framework to systematically quantify and generate insights for video ad storyline…
LLM Prompt Duel Optimizer: Efficient Label-Free Prompt Optimization
Yuanchen Wu, Saurabh Verma, Justin Lee +6
Large language models (LLMs) are highly sensitive to prompts, but most automatic prompt optimization (APO) methods assume access to ground-truth references (e.g., labeled validatio…
Characterizing and Minimizing Divergent Delivery in Meta Advertising Experiments
Gordon Burtch, Robert Moakler, Brett R. Gordon +2
Many digital platforms offer advertisers experimentation tools like Meta's Lift and A/B tests to optimize their ad campaigns. Lift tests compare outcomes between users eligible to…
Node Attribute Prediction on Multilayer Networks with Weighted and Directed Edges
Yiguang Zhang, Kristen Altenburger, Poppy Zhang +2
With the rapid development of digital platforms, users can now interact in endless ways from writing business reviews and comments to sharing information with their friends and fol…