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Alimama Tech

Jun 4, 2026 · Artificial Intelligence

ICML 2026 Highlights: Five Taotian Group Papers Pushing Multimodal AI Boundaries

The article showcases five ICML 2026 papers from the Taotian Group that tackle core multimodal AI challenges—interactive video try‑on, high‑resolution vision, e‑commerce video reasoning, sparse‑reward reinforcement learning, and curriculum learning for large language models—detailing their problem statements, novel solutions, and strong experimental results.

Curriculum LearningICML 2026Multimodal AI

0 likes · 15 min read

ICML 2026 Highlights: Five Taotian Group Papers Pushing Multimodal AI Boundaries

Alimama Tech

May 28, 2026 · Artificial Intelligence

13 KDD'26 Papers from Taobao: Scaling Laws, World Models and New AI Paradigms

The article highlights thirteen Taobao‑group papers accepted at KDD 2026, covering large‑model scaling laws, end‑to‑end generative recommendation, CTR prediction, interactive recommendation agents, LLM‑based pricing, robust auto‑bidding, two‑stage auctions, generative world models, multi‑attribution conversion, uplift modeling and long‑term causal estimation for e‑commerce systems.

CTR PredictionKDD 2026Scaling Laws

0 likes · 29 min read

13 KDD'26 Papers from Taobao: Scaling Laws, World Models and New AI Paradigms

Alimama Tech

May 28, 2026 · Artificial Intelligence

TAR: Multi‑Scale Trajectory Model Fixes Granularity Mismatch, Raising CTR >12%

The paper introduces the Trajectory Auto‑Regressive (TAR) model, which uses multi‑scale trajectory generation, a VQ‑VAE latent compression, and a state‑action fusion architecture to address granularity mismatch between fine‑grained decision steps and coarse‑grained feedback in online advertising, achieving over 12% CTR lift, smoother budget pacing, and faster inference compared to prior baselines.

Budget PacingMulti-Scale GenerationOnline Advertising

0 likes · 18 min read

TAR: Multi‑Scale Trajectory Model Fixes Granularity Mismatch, Raising CTR >12%

Alimama Tech

May 21, 2026 · Artificial Intelligence

Bridging LLMs' Social Gap: Graphia Uses Social Graphs as Supervision for Full Macro‑Micro Alignment

Graphia, a new LLM‑based social simulation framework, leverages social graph data as high‑quality supervision to jointly align microscopic interaction predictions and macroscopic network structures, achieving significant gains on TDGG and IDGG benchmarks across three real‑world datasets.

GraphiaLLMReinforcement Learning

0 likes · 12 min read

Bridging LLMs' Social Gap: Graphia Uses Social Graphs as Supervision for Full Macro‑Micro Alignment

Alimama Tech

May 14, 2026 · Artificial Intelligence

How LLM-Auction Lets Large Language Models Learn to Auction Marketing Content Within Answers

The article presents LLM-Auction, a novel AI‑native marketing mechanism that unifies ad allocation and answer generation by training large language models to conduct auctions directly on their output distribution, achieving higher allocation efficiency without extra inference cost.

AI-native advertisingLLM-Auctiongenerative auction

0 likes · 17 min read

How LLM-Auction Lets Large Language Models Learn to Auction Marketing Content Within Answers

Alimama Tech

May 7, 2026 · Artificial Intelligence

Dual‑Phase RL‑LLM Framework DARA for Few‑Shot Online Advertising Budget Allocation

The DARA framework splits online advertising budget allocation into a few‑shot LLM reasoning stage and a fine‑grained optimizer stage, enhanced by a dynamically updated RL‑fine‑tuning algorithm (GRPO‑Adaptive), achieving significantly lower ROI variance than traditional baselines in both real and simulated environments.

LLMOnline AdvertisingReinforcement Learning

0 likes · 16 min read

Dual‑Phase RL‑LLM Framework DARA for Few‑Shot Online Advertising Budget Allocation

Alimama Tech

Apr 9, 2026 · Artificial Intelligence

How LLM‑Powered AI Transforms Taobao Product Selection: From DeepSearch to Agentic RL

This article analyzes the challenges of traditional product selection on Taobao and presents an LLM‑driven solution that combines multi‑round online search, DeepSearch vs. WideSearch strategies, sample construction, SFT and RL training, and shows experimental results that improve relevance, diversity, and efficiency of the selected product set.

LLMe-commerceproduct selection

0 likes · 20 min read

How LLM‑Powered AI Transforms Taobao Product Selection: From DeepSearch to Agentic RL

Alimama Tech

Mar 26, 2026 · Industry Insights

How Alibaba’s Large User Model (LUM) Boosted CTR by 4.5% and Scaled to Billions of Parameters

The article analyzes the evolution from traditional modular recommendation models to a generative Large User Model (LUM), detailing its three‑stage paradigm, tokenization, training objectives, scaling‑law findings, offline and online experiments, and the AI‑infra innovations that enabled a 4.5% CTR lift in production.

CTR PredictionGenerative ModelingScaling Laws

0 likes · 18 min read

How Alibaba’s Large User Model (LUM) Boosted CTR by 4.5% and Scaled to Billions of Parameters

Alimama Tech

Mar 5, 2026 · Artificial Intelligence

How BiCB Revolutionizes Real‑Time Bidding for Live Ads with Light‑Weight Optimization

This article presents the BiCB (Binary Constrained Bidding) algorithm, a lightweight auto‑bidding solution for live advertising that combines optimal bidding formulas derived from linear‑programming dual analysis with traffic‑prediction statistics to achieve near‑optimal performance under budget and CPC constraints.

Online OptimizationTraffic Predictionauto-bidding

0 likes · 17 min read

How BiCB Revolutionizes Real‑Time Bidding for Live Ads with Light‑Weight Optimization

Alimama Tech

Feb 5, 2026 · Artificial Intelligence

Can Few-Shot Reinforcement Learning Supercharge Budget-Constrained Auto-Bidding?

This paper introduces ABPlanner, a few‑shot, context‑aware budget planner that enhances budget‑constrained auto‑bidding in online advertising by hierarchically allocating budgets across short‑term stages and training a sequential decision‑maker with deep reinforcement learning, achieving significant gains in simulated and real‑world A/B tests.

Online AdvertisingReinforcement Learningauto-bidding

0 likes · 13 min read

Can Few-Shot Reinforcement Learning Supercharge Budget-Constrained Auto-Bidding?