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Alimama Tech

Official Alimama tech channel, showcasing all of Alimama's technical innovations.

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Alimama Tech
Alimama Tech
Jan 24, 2024 · Artificial Intelligence

Hierarchical Masked 3D Diffusion Model for Video Outpainting

The Hierarchical Masked 3D Diffusion Model (M3DDM) introduces a masking‑based training strategy and cross‑attention with global video clips to achieve temporally consistent video outpainting, while a hybrid coarse‑to‑fine inference pipeline mitigates error accumulation, delivering state‑of‑the‑art results and deployment in Alibaba’s creative center.

3D diffusionACM MM2023AI video processing
0 likes · 12 min read
Hierarchical Masked 3D Diffusion Model for Video Outpainting
Alimama Tech
Alimama Tech
Jan 10, 2024 · Artificial Intelligence

Advances in Automated Bidding and Auction Mechanisms for Online Advertising

Advances in automated bidding for online ads have progressed from classic control and linear programming to reinforcement‑learning pipelines, offline and sustainable online RL, and finally generative‑model approaches, each enhancing decision strength, adaptability, and fairness while addressing simulation gaps, multi‑objective constraints, and real‑time efficiency.

Auction DesignGenerative AIOnline Advertising
0 likes · 25 min read
Advances in Automated Bidding and Auction Mechanisms for Online Advertising
Alimama Tech
Alimama Tech
Jan 3, 2024 · Artificial Intelligence

Alimama's 2023 Technical Highlights in AI and Advertising

Alimama’s 2023 newsletter details its AI‑driven advertising breakthroughs, from reinforcement‑learning bidding models and generative pricing (AIGB) to advanced auction mechanisms, historical‑data‑enhanced conversion‑rate prediction, and automated creative generation, highlighting related KDD/MM research papers and production‑level engineering implementations.

AIAdvertising TechnologyAlimama
0 likes · 5 min read
Alimama's 2023 Technical Highlights in AI and Advertising
Alimama Tech
Alimama Tech
Dec 21, 2023 · Information Security

Alibaba Mama Secure Data Hub: Cloud Architecture and Privacy-Preserving Advertising

Alibaba Mama’s Secure Data Hub delivers a privacy‑enhanced clean‑room for advertising by combining multi‑party computation, federated learning and differential privacy with encrypted operators on a Flink engine, offering cloud‑agnostic, scalable deployment that enables cross‑domain analytics while protecting raw user data and boosting ROI.

Data SecurityPrivacy Computingadvertising analytics
0 likes · 13 min read
Alibaba Mama Secure Data Hub: Cloud Architecture and Privacy-Preserving Advertising
Alimama Tech
Alimama Tech
Dec 14, 2023 · Artificial Intelligence

AI-Driven Content Risk Control: System Evolution and Optimization at Alibaba

Alibaba Mom’s AI‑driven content risk platform has evolved from simple rule‑matching to a data‑centric, serverless architecture that integrates large‑model acceleration, decision‑tree compilation, high‑throughput vector retrieval and elastic word‑matching, delivering sub‑100 ms text and sub‑1 s image moderation while remaining stable during peak promotional traffic.

AIContent moderationDevOps
0 likes · 25 min read
AI-Driven Content Risk Control: System Evolution and Optimization at Alibaba
Alimama Tech
Alimama Tech
Dec 7, 2023 · Industry Insights

How Privacy Computing Enables Cross‑Domain Ad Tracking and Asset Analysis

The 2023 Big Data “Galaxy” case competition highlighted Alibaba Mama and Jiahe Tech’s privacy‑computing based cross‑domain advertising tracking and whole‑domain asset analysis as an outstanding example, detailing the Secure Data Hub platform, its use of multi‑party secure computation, federated learning, differential privacy, and the resulting improvements in data flow, compliance, and marketing efficiency.

Data SecurityIndustry Case StudyPrivacy Computing
0 likes · 6 min read
How Privacy Computing Enables Cross‑Domain Ad Tracking and Asset Analysis
Alimama Tech
Alimama Tech
Nov 28, 2023 · Artificial Intelligence

Evolution of Alibaba's AI-Driven Advertising Decision Technologies

The article traces Alibaba’s Alimama platform from classic control‑based bidding through linear programming and reinforcement‑learning approaches to generative‑AI‑driven strategies, detailing how deep‑learning models, offline and sustainable online RL frameworks, and large‑language‑model‑based bidding reshape automated auctions, fairness, and scalability in e‑commerce advertising.

AIAuction DesignMachine Learning
0 likes · 38 min read
Evolution of Alibaba's AI-Driven Advertising Decision Technologies
Alimama Tech
Alimama Tech
Nov 22, 2023 · Artificial Intelligence

Robust Link Prediction under Bilateral Edge Noise via Robust Graph Information Bottleneck (RGIB)

The paper introduces Robust Graph Information Bottleneck (RGIB), a framework that jointly mitigates bilateral edge noise in link prediction by decoupling topology, label, and representation information, with two variants (RGIB‑SSL and RGIB‑REP) that achieve up to 12.9% AUC gains on benchmarks and have already boosted click‑through‑rate robustness and revenue in Alibaba’s advertising system.

RGIBRobustnessbilateral noise
0 likes · 13 min read
Robust Link Prediction under Bilateral Edge Noise via Robust Graph Information Bottleneck (RGIB)
Alimama Tech
Alimama Tech
Nov 15, 2023 · Industry Insights

How Alibaba’s Data‑Driven Marketing Drove Record‑Breaking Double 11 Results

The 2023 Tmall Double 11 campaign saw Alibaba’s data‑intelligent tools boost market share to 63.14%, lift GMV by over 6%, and help more than 200 brands achieve double‑digit growth through platforms like ShowMAX, Super Live, and Wanxiang AI, illustrating the power of integrated digital marketing in e‑commerce.

AlibabaData AnalyticsDouble 11
0 likes · 11 min read
How Alibaba’s Data‑Driven Marketing Drove Record‑Breaking Double 11 Results
Alimama Tech
Alimama Tech
Nov 15, 2023 · Artificial Intelligence

Hybrid Contrastive Constraints for Multi-Scenario Ad Ranking (HC²)

The HC² framework enhances multi‑scenario ad ranking by jointly applying a generalized contrastive loss on shared representations and an individual contrastive loss on scenario‑specific layers, using label‑aware positive sampling, diffusion‑noise negative sampling, and inverse‑similarity weighting, achieving consistent offline gains and up to 2.5% CVR and 3.7% GMV improvements in Alibaba’s live system.

Contrastive LearningMachine Learningad ranking
0 likes · 16 min read
Hybrid Contrastive Constraints for Multi-Scenario Ad Ranking (HC²)