CTR-Driven Advertising Image Generation Using Multimodal Large Language Models (CAIG)

The JD advertising team proposes a CTR‑driven advertising image generation framework (CAIG) that leverages multimodal large language models, a novel reward model, and product‑centric preference optimization to produce ad images with superior click‑through performance, validated by extensive offline and online experiments.

CTR optimizationReward modeladvertising image generation

0 likes · 10 min read

CTR-Driven Advertising Image Generation Using Multimodal Large Language Models (CAIG)

JD Tech Talk

Mar 13, 2025 · Artificial Intelligence

CTR-Driven Advertising Image Generation with Multimodal Large Language Models

This paper proposes CAIG, a novel method for generating high-CTR advertising images using multimodal large language models, combining reinforcement learning and preference optimization to align generated content with product features.

CTR predictionadvertising image generationmultimodal large language models

0 likes · 10 min read

CTR-Driven Advertising Image Generation with Multimodal Large Language Models

JD Cloud Developers

Mar 13, 2025 · Artificial Intelligence

Can Multimodal LLMs Boost Ad Click‑Through Rates? Introducing CTR‑Driven Image Generation

This paper presents a CTR‑driven advertising image generation framework that leverages multimodal large language models, reward modeling, and reinforcement learning to produce product‑centric ad visuals with higher click‑through performance, validated by extensive offline and online experiments.

CTR optimizationReward modeladvertising image generation

0 likes · 13 min read

Can Multimodal LLMs Boost Ad Click‑Through Rates? Introducing CTR‑Driven Image Generation

JD Tech Talk

Nov 14, 2024 · Artificial Intelligence

Can Human Feedback Make Advertising Image Generation Reliable? Introducing RFNet

This paper presents a multimodal Reliable Feedback Network (RFNet) and a consistency regularization method that use human feedback to automatically evaluate and fine‑tune diffusion models, dramatically increasing the usable rate of e‑commerce advertising images while preserving visual quality.

Computer VisionHuman FeedbackRFNet

0 likes · 8 min read

Can Human Feedback Make Advertising Image Generation Reliable? Introducing RFNet