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DataFunSummit
DataFunSummit
Nov 9, 2025 · Artificial Intelligence

How Kuaishou Boosted Ad Performance with Multimodal LLMs: COPE & LEARN Frameworks

This article reviews Kuaishou's two‑year exploration of large‑model techniques in advertising, detailing the challenges of content‑domain ad estimation, the use of multimodal and LLM technologies to harness full‑scope user behavior and external knowledge, and the COPE and LEARN frameworks that delivered measurable business gains.

AdvertisingKnowledge TransferMultimodal AI
0 likes · 6 min read
How Kuaishou Boosted Ad Performance with Multimodal LLMs: COPE & LEARN Frameworks
DataFunSummit
DataFunSummit
Oct 10, 2025 · Artificial Intelligence

How Kuaishou Boosted Ad Performance with Multimodal Large Models

This article reviews Kuaishou's two‑year exploration of large‑model techniques in advertising, outlining challenges in content‑domain ad estimation, introducing the COPE unified content representation framework and the LEARN LLM knowledge‑transfer approach, and showing how these innovations delivered tangible business gains.

AIAdvertisingKnowledge Transfer
0 likes · 5 min read
How Kuaishou Boosted Ad Performance with Multimodal Large Models
DataFunSummit
DataFunSummit
Oct 9, 2025 · Artificial Intelligence

How Kuaishou Boosted Ad Performance with Multimodal Large Models: COPE & LEARN

This article reviews Kuaishou's two‑year exploration of multimodal large‑model techniques for advertising, detailing challenges of fragmented user behavior, the COPE unified product representation framework, and the LEARN LLM knowledge‑transfer approach that together delivered measurable business gains.

AIAdvertisingKnowledge Transfer
0 likes · 6 min read
How Kuaishou Boosted Ad Performance with Multimodal Large Models: COPE & LEARN
Tencent Advertising Technology
Tencent Advertising Technology
Sep 3, 2025 · Artificial Intelligence

Boosting Ads Revenue: LFM4Ads’ Full‑Representation Multi‑Granular Transfer Raises GMV 2.45%

Tencent's LFM4Ads introduces a full‑representation, multi‑granular knowledge transfer framework that moves user, item, and cross representations from a large foundation model to downstream tasks, achieving up to 2.45% platform GMV uplift across more than ten advertising scenarios.

Knowledge Transferads recommendationfoundation model
0 likes · 12 min read
Boosting Ads Revenue: LFM4Ads’ Full‑Representation Multi‑Granular Transfer Raises GMV 2.45%
AsiaInfo Technology: New Tech Exploration
AsiaInfo Technology: New Tech Exploration
Jun 23, 2025 · Artificial Intelligence

How Generative Data‑Driven Model Distillation Boosts Large‑Model Performance and Cuts Compute

This article examines generative data‑driven model distillation as a technique that not only compresses large language models but also improves their accuracy, addresses data‑privacy constraints, and reduces computational costs, offering a practical roadmap and real‑world results from a corporate AI platform.

AI OptimizationKnowledge TransferMaaS platform
0 likes · 22 min read
How Generative Data‑Driven Model Distillation Boosts Large‑Model Performance and Cuts Compute
Model Perspective
Model Perspective
Jun 14, 2025 · Fundamentals

Unlocking the True Power of the Learning Compound Effect

The article explains the true nature of the compound effect in learning, outlining its financial origins, three essential elements, why many potential compounds fail, and four mechanisms—continuous use, transfer, feedback, and connection—that enable knowledge to generate lasting, exponential growth.

Continuous ImprovementKnowledge TransferLearning Theory
0 likes · 9 min read
Unlocking the True Power of the Learning Compound Effect
Data Thinking Notes
Data Thinking Notes
May 19, 2025 · Artificial Intelligence

How Model Distillation Shrinks Giant AI Models Without Losing Performance

This article explains model distillation—a technique that transfers knowledge from large teacher models to compact student models—covering its motivation, core principles, key steps, practical applications, and both its advantages and limitations, illustrating how AI can be made efficient without sacrificing performance.

AI compressionKnowledge Transfermodel distillation
0 likes · 10 min read
How Model Distillation Shrinks Giant AI Models Without Losing Performance
Architect's Guide
Architect's Guide
May 13, 2025 · Artificial Intelligence

DeepSeek Model Distillation Technology: Overview, Innovations, Architecture, Training, Performance, and Challenges

This article provides a comprehensive overview of DeepSeek's model distillation technology, detailing its definition, key innovations, architecture, training methods, performance gains, and the remaining challenges such as the implicit performance ceiling and multimodal data distillation.

AI OptimizationDeepSeekKnowledge Transfer
0 likes · 14 min read
DeepSeek Model Distillation Technology: Overview, Innovations, Architecture, Training, Performance, and Challenges
Top Architect
Top Architect
Feb 14, 2025 · Artificial Intelligence

DeepSeek Model Distillation: Principles, Innovations, Architecture, and Performance

This article provides an in‑depth overview of DeepSeek’s model distillation technology, covering its definition, core principles, innovative data‑model distillation integration, architecture design, training strategies, performance gains, and the challenges of scaling to multimodal data.

AI OptimizationDeepSeekKnowledge Transfer
0 likes · 16 min read
DeepSeek Model Distillation: Principles, Innovations, Architecture, and Performance
IT Architects Alliance
IT Architects Alliance
Feb 10, 2025 · Artificial Intelligence

DeepSeek Distillation Technology: Principles, Innovations, Performance, and Future Outlook

The article explains DeepSeek's model distillation technique, covering its fundamental knowledge‑transfer principles, unique innovations such as data‑model fusion and task‑specific strategies, impressive benchmark results, practical applications in edge and online inference, existing challenges, and future research directions.

AI OptimizationDeep LearningEdge Computing
0 likes · 15 min read
DeepSeek Distillation Technology: Principles, Innovations, Performance, and Future Outlook
Architect
Architect
Feb 9, 2025 · Artificial Intelligence

How DeepSeek’s Model Distillation Boosts AI Efficiency and Performance

This article provides an in‑depth analysis of DeepSeek’s model distillation technology, covering its definition, core principles, innovative strategies, architecture design, training optimizations, benchmark results, efficiency gains, and the remaining challenges of applying distillation to large language models and multimodal data.

AI efficiencyDeepSeekKnowledge Transfer
0 likes · 16 min read
How DeepSeek’s Model Distillation Boosts AI Efficiency and Performance
DataFunTalk
DataFunTalk
Nov 17, 2024 · Artificial Intelligence

Federated Learning and Data Security in the Era of Large Models: Research Overview and the FLAIR Platform

This presentation reviews recent research on data security and utilization in the large‑model era, covering privacy‑preserving federated learning, knowledge‑transfer techniques, prototype‑based modeling, multi‑model fusion methods such as FuseGen, and introduces the federated knowledge computing platform FLAIR for both horizontal and vertical federated scenarios.

FLAIRFederated LearningKnowledge Transfer
0 likes · 19 min read
Federated Learning and Data Security in the Era of Large Models: Research Overview and the FLAIR Platform
DataFunTalk
DataFunTalk
Jul 9, 2024 · Artificial Intelligence

Graph Knowledge Transfer and the Knowledge Bridge Learning Framework

This article presents an overview of graph knowledge transfer, discussing the data‑hungry problem, distribution shift in graph data, the Knowledge Bridge Learning (KBL) paradigm, the Bridged‑GNN implementation, experimental results across multiple scenarios, and future research directions.

Knowledge Transferbridged-GNNdomain adaptation
0 likes · 19 min read
Graph Knowledge Transfer and the Knowledge Bridge Learning Framework
Alipay Experience Technology
Alipay Experience Technology
May 9, 2024 · Artificial Intelligence

How Alipay Boosted Ad CTR and CPM with Cold‑Start Fixes, Knowledge Transfer, and Real‑Time Learning

This article details Alipay's advertising algorithm upgrades—including sample‑enhanced cold‑start mitigation, cross‑scene and user‑segmented knowledge transfer, and real‑time feature and online‑learning optimizations—that collectively lifted CTR, CPM, and overall business revenue.

AdvertisingCTR optimizationKnowledge Transfer
0 likes · 18 min read
How Alipay Boosted Ad CTR and CPM with Cold‑Start Fixes, Knowledge Transfer, and Real‑Time Learning
DataFunSummit
DataFunSummit
Apr 28, 2024 · Artificial Intelligence

Graph Knowledge Transfer: Methods, Practices, and the Knowledge Bridge Learning Framework

This article presents a comprehensive overview of graph knowledge transfer, covering its definition, the data‑hungry problem, distribution shift challenges, the Knowledge Bridge Learning (KBL) framework, the Bridged‑GNN model, extensive experiments on real‑world scenarios, and a concluding Q&A session.

Knowledge Transferdomain adaptationgraph learning
0 likes · 22 min read
Graph Knowledge Transfer: Methods, Practices, and the Knowledge Bridge Learning Framework
DataFunTalk
DataFunTalk
Feb 2, 2024 · Artificial Intelligence

Utilizing Negative Samples for Knowledge Distillation of Large Language Models

This paper presents a novel framework that leverages negative samples during large language model distillation through three stages—Negative Assistive Training, Negative Calibration Enhancement, and Adaptive Self‑Consistency—demonstrating significant accuracy gains on challenging mathematical reasoning benchmarks and improved generalization to out‑of‑distribution tasks.

Knowledge TransferLLM distillationchain-of-thought
0 likes · 13 min read
Utilizing Negative Samples for Knowledge Distillation of Large Language Models
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Dec 13, 2023 · Artificial Intelligence

Boosting Cross-Lingual Machine Reading Comprehension with X-STA: A New Knowledge Transfer Approach

The X-STA algorithm, introduced by Alibaba Cloud’s PAI and researchers from South China University of Technology, leverages gradient‑decomposed knowledge sharing, teacher‑guided attention, and multi‑level alignment to enhance cross‑lingual machine reading comprehension, achieving state‑of‑the‑art results on three multilingual MRC benchmarks.

Knowledge TransferX-STAcross-lingual
0 likes · 7 min read
Boosting Cross-Lingual Machine Reading Comprehension with X-STA: A New Knowledge Transfer Approach
Meituan Technology Team
Meituan Technology Team
Sep 14, 2023 · Artificial Intelligence

AdaScene: Adaptive Scenario Modeling for Multi‑Scene Recommendation in Meituan DSP

AdaScene introduces an adaptive scenario modeling framework for Meituan’s DSP that mitigates negative transfer and extreme data sparsity across heterogeneous display scenes by employing a knowledge‑transfer network with scene‑specific feature adaptation and gated expert sharing, alongside a gradient‑based scene‑aggregation process that clusters similar scenarios, yielding consistent performance gains for both high‑traffic and low‑traffic channels.

AIKnowledge Transferadaptive modeling
0 likes · 20 min read
AdaScene: Adaptive Scenario Modeling for Multi‑Scene Recommendation in Meituan DSP
DataFunTalk
DataFunTalk
May 24, 2023 · Artificial Intelligence

Graph Transfer Learning and VS-Graph: Knowledge Transferable Graph Neural Networks

This article reviews recent advances in graph transfer learning, introduces the novel VS-Graph scenario for knowledge transfer between dominant and silent nodes, and details the Knowledge Transferable Graph Neural Network (KTGNN) framework with domain‑adaptive feature completion, message passing, and transferable classifier modules, highlighting experimental results and future research directions.

AIKnowledge TransferVS-Graph
0 likes · 27 min read
Graph Transfer Learning and VS-Graph: Knowledge Transferable Graph Neural Networks