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Latest from Alimama Tech

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Alimama Tech

Apr 3, 2025 · Artificial Intelligence

UQABench: A Personalized QA Benchmark for Evaluating User Embeddings in LLM‑Driven Recommendation Systems

UQABench introduces the first benchmark for assessing high‑density user embeddings that serve as soft prompts in LLM‑driven recommendation, featuring a three‑stage pre‑train‑align‑evaluate pipeline, seven personalized QA tasks, and findings that transformer encoders, side‑information, simple linear adapters, and larger models markedly improve accuracy while cutting input tokens to about five percent.

AILLMRecommendation Systems

0 likes · 12 min read

UQABench: A Personalized QA Benchmark for Evaluating User Embeddings in LLM‑Driven Recommendation Systems

Alimama Tech

Mar 28, 2025 · Artificial Intelligence

How Alibaba’s Taobao AI Models Revolutionize E‑Commerce Recommendations and Bidding

Alibaba’s Taobao Group unveiled its AIGX technology suite, including the RecGPT recommendation model, the AIGB generative bidding system, and a new AI‑generated video engine, detailing open‑source benchmarks, NeurIPS workshop participation, and measurable ROI improvements for e‑commerce advertising.

AIGenerative BiddingRecommendation Systems

0 likes · 5 min read

How Alibaba’s Taobao AI Models Revolutionize E‑Commerce Recommendations and Bidding

Alimama Tech

Mar 14, 2025 · Artificial Intelligence

Advances in Search Advertising Models with Large Language Models (2024)

In 2024 Alibaba Mama outlines how large‑language models transform search advertising through a three‑line scaling roadmap—explicit inductive‑bias design, implicit compute growth, and auxiliary CV/NLP advances—implemented via a pre‑train/post‑train/CTR paradigm and the LUM user‑behavior model, promising gains in relevance, recall, and real‑time serving while highlighting inference efficiency challenges.

CTR predictionScaling Lawlarge language models

0 likes · 25 min read

Advances in Search Advertising Models with Large Language Models (2024)

Alimama Tech

Mar 12, 2025 · Big Data

Design and Evolution of Alibaba Advertising Real-Time Data Warehouse

Alibaba Mama’s advertising platform migrated from a monolithic Flink‑Kafka pipeline to a layered Paimon lakehouse, adding DWS upsert support and multi‑layer storage, which delivers minute‑level data freshness, cuts latency by 2.5 hours, reduces resource use over 40 %, halves development effort and achieves ≥99.9 % availability.

AdvertisingAlibabaFlink

0 likes · 18 min read

Design and Evolution of Alibaba Advertising Real-Time Data Warehouse

Alimama Tech

Feb 21, 2025 · Industry Insights

How Paimon + Dolphin Transform Alibaba’s Brand Data Warehouse for Real‑Time Insights

This article analyzes the challenges of Alibaba Mama's brand advertising data warehouse built on a Lambda architecture, introduces Apache Paimon lake storage and Dolphin OLAP engine as a unified lakehouse solution, details implementation steps, performance gains, and business benefits across multiple advertising scenarios.

Data WarehouseDolphinOLAP

0 likes · 15 min read

Alimama Tech

Feb 12, 2025 · Artificial Intelligence

HighService: A High‑Performance Pythonic AI Service Framework for Model Inference and Global Resource Scheduling

HighService, Alibaba’s Pythonic AI service framework, accelerates large‑model inference and maximizes GPU utilization by separating CPU‑GPU processes, offering out‑of‑the‑box quantization, parallelism and caching, and dynamically reallocating idle GPUs across clusters through a master‑worker scheduler to keep online latency low while boosting offline throughput for diffusion and LLM workloads.

AI ServiceHigh PerformanceModel Inference

0 likes · 16 min read

HighService: A High‑Performance Pythonic AI Service Framework for Model Inference and Global Resource Scheduling

Alimama Tech

Jan 8, 2025 · Artificial Intelligence

Model-Based Reinforcement Learning Auto‑Bidding Algorithms for Online Advertising

The paper introduces a model‑based reinforcement‑learning auto‑bidding framework that learns a neural‑network environment model from real logs, generates confidence‑aware virtual data fused with real data, and employs the COMBO+MICRO stabilizer and a Lagrange‑dual method for ROI‑constrained bidding, delivering up to 6.8 % higher consumption, 5 % GMV growth and 3.7 % ROI improvement on Alibaba’s platform.

auto-biddingbudget constrained biddingmodel-based RL

0 likes · 22 min read

Model-Based Reinforcement Learning Auto‑Bidding Algorithms for Online Advertising

Alimama Tech

Dec 25, 2024 · Artificial Intelligence

WiS Platform: Evaluating LLM Multi-Agent Systems via Game-Based Analysis

The WiS Platform provides a game‑based environment for benchmarking large language models in multi‑agent settings, measuring reasoning, deception and collaboration through dynamic scenarios, offering fair experimental design, real‑time competition, visualizations, detailed metrics, and open‑source tools, with GPT‑4o outperforming other models such as Qwen2.5‑72B‑Instruct.

AI evaluationDefense StrategiesGame-Based Testing

0 likes · 8 min read

WiS Platform: Evaluating LLM Multi-Agent Systems via Game-Based Analysis

Alimama Tech

Dec 25, 2024 · Artificial Intelligence

Contextual Generative Auction with Permutation-level Externalities for Online Advertising

The paper introduces Contextual Generative Auction (CGA), a generative framework that directly optimizes ad placements while modeling permutation‑level externalities, decouples allocation from payment learning, and achieves near‑optimal Myerson‑style outcomes, delivering up to 3.2% higher RPM, 1.4% more CTR, 6.4% GMV growth, and 3.5% increased advertiser ROI in large‑scale Taobao experiments.

Externalitiesauction theorygenerative models

0 likes · 18 min read

Contextual Generative Auction with Permutation-level Externalities for Online Advertising

Alimama Tech

Dec 17, 2024 · Artificial Intelligence

Auto‑Bidding in Large‑Scale Auctions: The AIGB Paradigm and the AuctionNet Benchmark

At NeurIPS 2024, Alibaba's AliMama workshop introduced AIGB, a generative-model based auto-bidding solution, and released AuctionNet benchmark with billions of records; the competition attracted 1,861 participants across generative and uncertainty tracks, with winners earning prizes and internships, highlighting broader applications beyond advertising.

AuctionNetNeurIPSdecision intelligence

0 likes · 12 min read

Auto‑Bidding in Large‑Scale Auctions: The AIGB Paradigm and the AuctionNet Benchmark