LLM-HYPER treats an LLM as a hypernetwork that outputs feature-wise weights for a linear CTR model from few-shot multimodal ad examples, achieving 55.9% better NDCG@10 than cold-start baselines and successful production deployment.
InProceedings of the ACM on Web Con- ference 2025, pages 3850–3862
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
LLM-HYPER: Generative CTR Modeling for Cold-Start Ad Personalization via LLM-Based Hypernetworks
LLM-HYPER treats an LLM as a hypernetwork that outputs feature-wise weights for a linear CTR model from few-shot multimodal ad examples, achieving 55.9% better NDCG@10 than cold-start baselines and successful production deployment.