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Nov 28, 2025 · Artificial Intelligence

How JD Ads Uses Large Language Models to Transform Advertising

This article details JD Advertising's shift from generic to domain‑specific large models, the design of AI‑driven ad agents, the end‑to‑end GRAM retrieval‑alignment system, CTR‑guided AIGC for creatives, ultra‑low‑latency inference techniques, and ARM‑based optimizations that together reshape modern ad marketing.

CTR optimizationIntelligent agentsLarge Language Models

0 likes · 19 min read

How JD Ads Uses Large Language Models to Transform Advertising

JD Tech

Mar 26, 2025 · Artificial Intelligence

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 optimizationReinforcement LearningReward model

0 likes · 10 min read

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

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

Alipay Experience Technology

May 9, 2024 · Artificial Intelligence

How Alipay Boosted Ad CTR and CPM with Cold‑Start Fixes, Knowledge Transfer, and Real‑Time Learning

This article details Alipay's advertising algorithm upgrades—including sample‑enhanced cold‑start mitigation, cross‑scene and user‑segmented knowledge transfer, and real‑time feature and online‑learning optimizations—that collectively lifted CTR, CPM, and overall business revenue.

AdvertisingCTR optimizationKnowledge Transfer

0 likes · 18 min read

How Alipay Boosted Ad CTR and CPM with Cold‑Start Fixes, Knowledge Transfer, and Real‑Time Learning

Baidu Geek Talk

Jan 17, 2024 · Industry Insights

How Baidu Boosted Search Push Clicks with Model Calibration and DeltaCTR Strategies

This article details Baidu Search's personalized push system, covering challenges in material selection and user targeting, the end‑to‑end workflow, model accuracy improvements, pCTR calibration techniques, deltaCTR‑based ranking, and the combined offline‑online experiments that significantly raised both CTR and DAU.

BaiduCTR optimizationdeltaCTR

0 likes · 16 min read

How Baidu Boosted Search Push Clicks with Model Calibration and DeltaCTR Strategies

DataFunTalk

Nov 2, 2021 · Artificial Intelligence

Personalized Recommendation and Advertising Algorithms for E‑commerce: Business Overview, Recall and Ranking Optimization, Multi‑Task Modeling, and Future Directions

This article presents a comprehensive technical overview of JD.com’s e‑commerce recommendation and advertising systems, covering business scenarios, recall optimizations (profile and similarity‑based), multi‑task ranking improvements, sample weighting, multi‑model ensembles, PID‑based CPC control, conversion‑delay modeling, and the achieved performance gains and future research plans.

CTR optimizationRecommendation Systemse‑commerce

0 likes · 18 min read

Personalized Recommendation and Advertising Algorithms for E‑commerce: Business Overview, Recall and Ranking Optimization, Multi‑Task Modeling, and Future Directions

Alibaba Cloud Developer

Dec 12, 2018 · Artificial Intelligence

Tackling Pseudo-Exposure in Mobile E-Commerce: A Contextual Multiple-Play Bandit Approach

To address the pseudo-exposure problem that reduces click-through rates in mobile e-commerce recommendation, the authors model the task as a contextual multiple-play bandit, propose weighted sample and similarity-enhanced linear reward extensions, provide sublinear regret proofs, and demonstrate significant CTR gains on real Taobao data.

Bandit AlgorithmsCTR optimizationcontextual multi-play

0 likes · 30 min read

Tackling Pseudo-Exposure in Mobile E-Commerce: A Contextual Multiple-Play Bandit Approach