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Latest from Alimama Tech

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Alimama Tech

Jul 15, 2024 · Artificial Intelligence

Why Auto‑Bidding in Large‑Scale Auctions Is the Hottest NeurIPS Challenge

The article explains how NeurIPS ranks among top AI conferences, introduces the newly selected “Auto‑Bidding in Large‑Scale Auctions” competition, outlines its technical background, four generations of bidding strategies—from classic control to generative models—and details the competition’s tracks, rewards, and how researchers can participate.

AdvertisingCompetitionNeurIPS

0 likes · 12 min read

Why Auto‑Bidding in Large‑Scale Auctions Is the Hottest NeurIPS Challenge

Alimama Tech

Jul 11, 2024 · Artificial Intelligence

Efficient Local Search for Guaranteed Display Advertising Inventory Allocation with Multilinear Constraints

The paper introduces LS‑IMP, a two‑stage local‑search algorithm with four novel operators that efficiently solves guaranteed‑delivery advertising inventory allocation under non‑convex multilinear media‑preference constraints, consistently outperforming commercial solvers and heuristics in solution quality and speed on real‑world datasets.

Online Advertisingalgorithminventory allocation

0 likes · 17 min read

Efficient Local Search for Guaranteed Display Advertising Inventory Allocation with Multilinear Constraints

Alimama Tech

Jul 2, 2024 · Artificial Intelligence

NeurIPS 2024 Competition: Auto-Bidding in Large-Scale Auctions

The 2024 NeurIPS Competition, organized by Peking University's PAAI lab and Alibaba‑Mama, challenges teams to build auto‑bidding agents—using generative models for the AIGB Track or handling uncertainty for the General Track—to maximize ad performance in large‑scale auctions, with registration open until August 8 and prize pools up to $6,000 per track.

CompetitionNeurIPSauction

0 likes · 4 min read

NeurIPS 2024 Competition: Auto-Bidding in Large-Scale Auctions

Alimama Tech

Jun 21, 2024 · Artificial Intelligence

CausalMMM: Learning Causal Structure for Marketing Mix Modeling

CausalMMM introduces an encoder‑decoder framework that automatically discovers heterogeneous, interpretable causal graphs among advertising channels while modeling temporal decay and saturation, using Granger‑based variational inference, and achieves over 5.7% improvement in causal structure learning and significant GMV prediction gains on Alibaba’s data.

marketing mix modelingtime-series-forecastingvariational inference

0 likes · 16 min read

CausalMMM: Learning Causal Structure for Marketing Mix Modeling

Alimama Tech

Jun 13, 2024 · Artificial Intelligence

Calibration-compatible Listwise Distillation of Privileged Features for CTR Prediction

The article describes Alibaba's approach to distilling privileged features for CTR prediction using a calibration-compatible listwise distillation loss (CLID) that normalizes teacher and student outputs within sessions to align top‑ranking probabilities, improving both accuracy and ranking while preserving calibration.

AI in advertisingCTR predictionListwise distillation

0 likes · 14 min read

Calibration-compatible Listwise Distillation of Privileged Features for CTR Prediction

Alimama Tech

May 29, 2024 · Artificial Intelligence

Alibaba Mama Team Papers Accepted at KDD 2024

Alibaba’s Mama technical team secured four paper acceptances at the prestigious KDD 2024 conference in Barcelona, presenting advances such as a diffusion‑based generative bidding model, truthful combinatorial bandit mechanisms for two‑stage ad auctions, bi‑objective contract allocation for guaranteed delivery advertising, and a fast local‑search algorithm for complex contract constraints.

AIAdvertisingBandit

0 likes · 8 min read

Alibaba Mama Team Papers Accepted at KDD 2024

Alimama Tech

May 29, 2024 · Artificial Intelligence

Mixture of Multi‑Modal Experts for Advertising Recall

The Mixed‑Modal Expert Model combines ID features with image and text embeddings through optimized representations and conditional output fusion, dramatically improving advertising recall—especially for long‑tail items—and delivering measurable gains in click‑recall, revenue, CTR, and page views in large‑scale online tests.

ModelRecallmachine learning

0 likes · 15 min read

Mixture of Multi‑Modal Experts for Advertising Recall

Alimama Tech

May 15, 2024 · Artificial Intelligence

CCF‑Alibaba Mama Technology Fund Launch and Large‑Model Forum (May 18, 2024)

On May 18, 2024, CCF and Alibaba Mama will unveil the CCF‑Alibaba Mama Technology Fund—a global academia‑industry platform targeting next‑generation AI algorithms and large‑model research through ten projects in e‑commerce, knowledge‑enhanced generation, and legal AI, with a livestreamed forum featuring a keynote by Prof. Zhang Qi on boosting task performance.

AlibabaArtificial IntelligenceCCF

0 likes · 5 min read

CCF‑Alibaba Mama Technology Fund Launch and Large‑Model Forum (May 18, 2024)

Alimama Tech

May 15, 2024 · Artificial Intelligence

EcomXL: Optimizing SDXL for Large‑Scale E‑commerce Image Generation

EcomXL enhances SDXL for large‑scale e‑commerce image generation by leveraging tens of millions of curated images, a two‑stage fine‑tuning with denoising‑weighted distillation and layer‑wise fusion, specialized ControlNets for inpainting and soft‑edge consistency, and the SLAM inference accelerator to achieve sub‑second generation while boosting visual quality and adoption metrics.

AIGCControlNetEcomXL

0 likes · 15 min read

EcomXL: Optimizing SDXL for Large‑Scale E‑commerce Image Generation

Alimama Tech

May 6, 2024 · Artificial Intelligence

CCF‑Alibaba Mama Technology Fund Launch and Large‑Model Forum (May 18, 2024)

On May 18 in Ningbo, CCF and Alibaba Mama unveiled the CCF‑Alibaba Mama Technology Fund—a global academia‑industry platform targeting next‑generation AI algorithms and large‑model research through ten projects in e‑commerce, tool generation, and legal services—accompanied by a keynote on boosting large‑model task performance and open registration for scholars.

Academic-Industry CollaborationAlibabaArtificial Intelligence

0 likes · 5 min read