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Alimama Tech

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

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Recent Articles

Latest from Alimama Tech

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Alimama Tech
Alimama Tech
Nov 11, 2025 · Artificial Intelligence

Accelerating LLM RL with Async Training, Mini‑Critics, and Attention Rewards

This article introduces the 3A collaborative framework—Async architecture, Asymmetric PPO mini‑critics, and an attention‑based reasoning rhythm—demonstrating how decoupled, fine‑grained parallel training and structure‑aware reward allocation dramatically improve efficiency, scalability, and interpretability of reinforcement learning for large language models.

Asynchronous TrainingAttention MechanismsLarge Language Models
0 likes · 23 min read
Accelerating LLM RL with Async Training, Mini‑Critics, and Attention Rewards
Alimama Tech
Alimama Tech
Nov 11, 2025 · Artificial Intelligence

Industrial-Scale Graph Learning: Boosting Ad ROI and Winning Beijing’s Science Award

The award‑winning industrial graph learning system developed by Peking University and Alibaba Mama combines novel dynamic graph embedding and GNN techniques, scales to millions of merchants, and has driven over 12% ad ROI improvement while publishing dozens of top‑conference papers.

AI researchAdvertising OptimizationGraph Neural Networks
0 likes · 6 min read
Industrial-Scale Graph Learning: Boosting Ad ROI and Winning Beijing’s Science Award
Alimama Tech
Alimama Tech
Oct 29, 2025 · Artificial Intelligence

LLM Breakthroughs at EMNLP 2025: Embedding Compression, Complex Instructions, Knowledge Scaling

EMNLP 2025 in Suzhou showcases Taobao's booth featuring four cutting‑edge AI papers that introduce a novel embedding compression framework, an automatic iterative refinement method for complex instruction generation, a knowledge infusion scaling law for large language models, and a video caption optimization approach for text‑to‑video generation.

Large Language Modelsembedding compressioninstruction generation
0 likes · 7 min read
LLM Breakthroughs at EMNLP 2025: Embedding Compression, Complex Instructions, Knowledge Scaling
Alimama Tech
Alimama Tech
Oct 22, 2025 · Artificial Intelligence

How Alibaba’s AIGC Model Revolutionizes Virtual Fashion Try‑On

This article details Alibaba’s Taobao Star fashion AIGC model, explaining its data pipeline, captioning strategy, multi‑stage training, and impressive virtual try‑on results for users and merchants, while showcasing model‑based and model‑free generation and pose‑transfer capabilities.

AIAIGCComputer Vision
0 likes · 11 min read
How Alibaba’s AIGC Model Revolutionizes Virtual Fashion Try‑On
Alimama Tech
Alimama Tech
Oct 15, 2025 · Artificial Intelligence

How Alibaba’s Taobao Starry Model Delivers Precise, Consistent E‑commerce Image Edits

Alibaba’s Taobao Starry Image Editing model tackles the e‑commerce challenge of maintaining visual consistency by introducing a high‑fidelity, plug‑in architecture, a million‑scale consistency dataset, and multi‑stage multilingual training, enabling precise, controllable edits without altering product layout or background.

Data EngineeringImage EditingPlug‑in Architecture
0 likes · 10 min read
How Alibaba’s Taobao Starry Model Delivers Precise, Consistent E‑commerce Image Edits
Alimama Tech
Alimama Tech
Oct 1, 2025 · Artificial Intelligence

How RecIS Revolutionizes Large‑Scale Sparse‑Dense Recommendation Training

RecIS is an open‑source, PyTorch‑based unified framework designed for ultra‑large‑scale sparse‑dense computation in recommendation systems, offering a full solution for training models with massive samples, multimodal inputs, and large embeddings, and demonstrating significant performance gains over TensorFlow and TorchRec in production deployments.

PyTorchdeep learning frameworklarge-scale AI
0 likes · 24 min read
How RecIS Revolutionizes Large‑Scale Sparse‑Dense Recommendation Training
Alimama Tech
Alimama Tech
Sep 24, 2025 · Information Security

Differential Privacy Explained: Theory, Techniques, and Real-World AI Deployments

This article provides a comprehensive overview of differential privacy, covering its mathematical foundations, evolution from theory to engineering, classification of privacy mechanisms, practical implementation cases such as Alibaba's Secure Data Hub, and diverse application scenarios across healthcare, finance, location analytics, and energy forecasting.

AI ComplianceData SecurityDifferential Privacy
0 likes · 23 min read
Differential Privacy Explained: Theory, Techniques, and Real-World AI Deployments
Alimama Tech
Alimama Tech
Sep 17, 2025 · Artificial Intelligence

How Federated Learning Balances Privacy and Collaboration in AI

Federated Learning enables multiple parties to collaboratively train a global AI model without sharing raw data, using techniques like local training, encrypted parameter exchange, and secure aggregation, while addressing privacy, communication efficiency, heterogeneity, and incentive challenges across horizontal, vertical, and transfer learning scenarios.

Horizontal FLSecure AggregationVertical FL
0 likes · 24 min read
How Federated Learning Balances Privacy and Collaboration in AI
Alimama Tech
Alimama Tech
Sep 3, 2025 · Artificial Intelligence

Privacy-Preserving Machine Learning: Balancing Data Utility and Confidentiality

Privacy-Preserving Machine Learning (PPML) integrates cryptographic techniques such as federated learning, differential privacy, homomorphic encryption, and secure multi-party computation to enable model training and inference on encrypted or distributed data, thereby breaking data silos while safeguarding privacy across sectors like healthcare, finance, and advertising.

Homomorphic Encryptionfederated learningmachine learning
0 likes · 18 min read
Privacy-Preserving Machine Learning: Balancing Data Utility and Confidentiality