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May 15, 2026 · Artificial Intelligence

2026 Big Data Challenge Announces Monthly Star Winners and Shares Winning Teams’ Insights

The 2026 China University Computer Competition – Big Data Challenge reveals the Monthly Star award winners, each receiving 800 RMB, and presents detailed experience reports from the top teams covering feature engineering, model selection, training validation, and ensemble strategies for stock prediction.

Big DataModel FusionStock Prediction

0 likes · 7 min read

2026 Big Data Challenge Announces Monthly Star Winners and Shares Winning Teams’ Insights

AI Explorer

Mar 17, 2026 · Artificial Intelligence

Mistral Small 4 Launch and Nvidia Nemotron Alliance Signal AI Power Shift

Mistral AI’s newly released Small 4 model merges the capabilities of its three flagship models into a more efficient architecture, and its entry into Nvidia’s Nemotron alliance marks a strategic shift toward an open‑source AI ecosystem that could challenge the dominance of closed‑source giants like OpenAI and Google.

AI ecosystemMistral AIModel Fusion

0 likes · 7 min read

Mistral Small 4 Launch and Nvidia Nemotron Alliance Signal AI Power Shift

Baobao Algorithm Notes

Apr 27, 2025 · Artificial Intelligence

How Model Fusion Cut LLM Chain‑of‑Thought Length by 40% Without Fine‑Tuning

A small tech firm, tngtech, released an open‑source model fusion called DeepSeek‑R1T‑Chimera that merges R1 inference with V3‑0324 without fine‑tuning, distillation, or prompts, achieving the same intelligence as R1 while reducing token output by 40% and speeding up inference.

DeepSeekLLMModel Fusion

0 likes · 4 min read

How Model Fusion Cut LLM Chain‑of‑Thought Length by 40% Without Fine‑Tuning

Baobao Algorithm Notes

Mar 10, 2024 · Artificial Intelligence

Unlocking Large Model Power: 5 Effective Model Fusion Techniques Explained

This article examines why ensemble methods are crucial for large language models, outlines five core fusion strategies—including model integration, probability integration, graft learning, crowdsourced voting, and Mixture of Experts—provides implementation details, pseudo‑code, and discusses practical challenges and recent research advances.

AI researchMixture of ExpertsModel Fusion

0 likes · 16 min read

Unlocking Large Model Power: 5 Effective Model Fusion Techniques Explained

DataFunSummit

Dec 15, 2023 · Artificial Intelligence

Integrating Large Language Models into Recommender Systems: Opportunities, Methods, and Challenges

This article explores how large language models can be incorporated into recommender systems, discussing background challenges, specific integration points across the recommendation pipeline, practical implementation methods, experimental results, and future research directions, while highlighting industrial considerations and potential improvements.

Industrial ApplicationsLLMModel Fusion

0 likes · 20 min read

Integrating Large Language Models into Recommender Systems: Opportunities, Methods, and Challenges

DeWu Technology

Dec 27, 2021 · Artificial Intelligence

Multi-Objective Modeling and Practice in DeWu Community Recommendation System

DeWu Community’s recommendation system progressed from single‑objective CTR modeling to a multi‑objective framework that combines independent models for dwell time, video completion and user interactions via score‑fusion, ranking‑learning and multi‑task architectures with shared parameters and gradient‑blocking, delivering higher engagement and retention.

CTRModel Fusionmulti-task learning

0 likes · 15 min read

Multi-Objective Modeling and Practice in DeWu Community Recommendation System

iQIYI Technical Product Team

Jun 25, 2021 · Artificial Intelligence

Multi-Objective Optimization in Short Video Recommendation at iQIYI

iQIYI improves short‑video recommendation by applying multi‑objective optimization—weighting clicks by watch duration, fusing separate click and watch‑time models, employing multi‑task learning with ESMM/MMOE and Pareto‑guided PSO hyper‑parameter search—delivering 7%+ watch‑time growth, 20%+ interaction gains, and 1.5‑3% CTR lifts while planning cross‑scene learning and further model refinements.

Model FusionParticle Swarm Optimizationmulti-task learning

0 likes · 14 min read

Multi-Objective Optimization in Short Video Recommendation at iQIYI

NetEase Media Technology Team

Apr 13, 2021 · Artificial Intelligence

Applying BERT for News Timeliness Classification at NetEase

The article describes how NetEase adapts a pre‑trained BERT model to classify news articles into ultra‑short, short, or long timeliness categories by combining rule‑based strong and weak time cues, key‑sentence extraction, domain‑embedding fusion and multi‑layer semantic aggregation, achieving accurate and interpretable predictions for its platform.

BERTModel FusionNLP

0 likes · 12 min read

Applying BERT for News Timeliness Classification at NetEase

58 Tech

Mar 1, 2021 · Artificial Intelligence

Intelligent QABot for 58.com: Classification and Retrieval Model Exploration

This article describes how 58.com’s AI Lab built and continuously improved the QABot intelligent customer‑service system by designing classification and retrieval models, evaluating FastText, LSTM‑DSSM, BERT and a self‑developed SPTM framework, and finally fusing them to boost answer rates and user experience.

AI chatbotBERTModel Fusion

0 likes · 9 min read

Intelligent QABot for 58.com: Classification and Retrieval Model Exploration

Tencent Advertising Technology

Jul 16, 2020 · Artificial Intelligence

Interview with DYG Team Member Wang He: Team Story and Model Fusion Strategies for the Competition

In this interview, DYG team member Wang He introduces his teammates, explains why they formed the team, and shares detailed model‑fusion techniques—including input variation, diverse model architectures, and training‑target differences—to boost competition scores during the final stage.

AIModel FusionNLP

0 likes · 6 min read

Interview with DYG Team Member Wang He: Team Story and Model Fusion Strategies for the Competition

DataFunTalk

Jun 5, 2020 · Artificial Intelligence

Introducing qa_match: An Open‑Source Lightweight Question‑Answer Matching Tool Based on Deep Learning

The article presents qa_match, a TensorFlow‑based open‑source QA matching system that combines BiLSTM‑attention domain classification with DSSM intent matching, explains its architecture, training workflow, features, future roadmap, and how developers can contribute to the project.

BiLSTMDSSMDeep Learning

0 likes · 10 min read

Introducing qa_match: An Open‑Source Lightweight Question‑Answer Matching Tool Based on Deep Learning

Qunar Tech Salon

Apr 29, 2019 · Artificial Intelligence

Multi‑Level Deep Model Fusion for Fake News Detection Using BERT – Winning Solution of WSDM Cup 2019

The article details the Travel team's award‑winning solution for the WSDM Cup 2019 fake‑news detection task, describing data analysis, preprocessing, label‑propagation augmentation, a BERT‑based baseline, a three‑stage multi‑level model‑fusion framework, experimental results, and future directions.

BERTModel FusionNLP

0 likes · 12 min read

Multi‑Level Deep Model Fusion for Fake News Detection Using BERT – Winning Solution of WSDM Cup 2019

iQIYI Technical Product Team

Mar 22, 2019 · Artificial Intelligence

Experience Report of the 2018 iQIYI Multimodal Video Person Identification Challenge (WitcheR Team)

The WitcheR team won the 2018 iQIYI multimodal video person identification challenge by building a fast pipeline that combined a custom face‑and‑keypoint detector, ArcFace‑trained face embeddings, scene classification, and a three‑layer MLP with several training tricks, achieving a final mAP of 88.6 % and demonstrating the value of rapid idea validation and open‑sourced code for future challenges.

MLPModel Fusioncompetition

0 likes · 12 min read

Experience Report of the 2018 iQIYI Multimodal Video Person Identification Challenge (WitcheR Team)

Meituan Technology Team

Feb 21, 2019 · Artificial Intelligence

Fake News Detection with Multi‑level BERT Fusion at WSDM Cup 2019

In the WSDM Cup 2019 fake-news detection challenge, the Meituan Travel team secured second place by combining extensive data analysis, Chinese-English BERT fine-tuning, label-propagation augmentation, and a three-level fusion framework—blending, stacking, and linear regression—that lifted weighted accuracy to 0.88156.

BERTModel FusionNLP

0 likes · 16 min read

Fake News Detection with Multi‑level BERT Fusion at WSDM Cup 2019

DataFunTalk

Sep 27, 2018 · Artificial Intelligence

Applying Machine Learning in Shumei's Business: Supervised, Unsupervised, and Reinforcement Learning Cases

The article presents a comprehensive overview of how Shumei Technology leverages machine learning—including supervised, unsupervised, and reinforcement learning methods—across its credit scoring, fraud detection, advertising, and audio content moderation services, highlighting practical challenges, model fusion techniques, and future research directions.

Model Fusionreinforcement learning

0 likes · 12 min read

Applying Machine Learning in Shumei's Business: Supervised, Unsupervised, and Reinforcement Learning Cases

Tencent Advertising Technology

Mar 27, 2018 · Artificial Intelligence

Insights and Lessons from the First Tencent Social Advertising University Algorithm Competition

The article shares a Beijing University team's experience in the first Tencent Social Advertising algorithm contest, detailing their fourth‑place finish, best‑presentation award, and five key strategies—including business‑logic analysis, model innovation, multi‑model fusion, teamwork, and leveraging existing research—to improve conversion‑rate prediction performance.

AdvertisingModel Fusioncompetition

0 likes · 6 min read

Insights and Lessons from the First Tencent Social Advertising University Algorithm Competition

JD Retail Technology

Dec 11, 2017 · Big Data

Data Model Component Management Platform: Functions and Practices

The presentation introduces JD's Data Model Component Management Platform, detailing its four core functions—risk control, effect evaluation, model fusion, and multi‑scenario application—while explaining how these capabilities improve model reliability, commercial value, and operational efficiency across numerous business products.

JDModel Fusiondata-model

0 likes · 8 min read

Data Model Component Management Platform: Functions and Practices

Tencent Advertising Technology

Jun 23, 2017 · Artificial Intelligence

Weekly Champion nju_newbiew Shares Competition Experience and Technical Insights

The nju_newbiew team, winners of the weekly champion in Tencent Social Ads University Algorithm Competition, recount their data processing, offline validation, feature engineering, and model strategies, highlighting practical machine‑learning lessons while also providing competition announcements and contact information.

AIModel Fusioncompetition

0 likes · 5 min read

Weekly Champion nju_newbiew Shares Competition Experience and Technical Insights

Ctrip Technology

May 6, 2017 · Artificial Intelligence

Customer Churn Prediction Using Machine Learning: Feature Engineering, XGBoost, and Model Fusion

This article explains how to predict customer churn by analyzing competition data, extracting and engineering features, applying GBDT‑based XGBoost models, tuning hyper‑parameters, and improving performance through bagging and stacking model fusion techniques.

Customer ChurnModel FusionXGBoost

0 likes · 15 min read

Customer Churn Prediction Using Machine Learning: Feature Engineering, XGBoost, and Model Fusion

Ctrip Technology

Jul 29, 2016 · Artificial Intelligence

Applying Deep Learning to Sogou Mobile Search Advertising: Multi‑Model Fusion for CTR Prediction

This article presents how deep learning techniques are applied to Sogou's mobile search advertising, detailing the system architecture, feature design, multi‑model fusion strategies, engineering implementation, evaluation metrics, and future directions for improving CTR prediction performance.

CTR predictionDeep LearningModel Fusion

0 likes · 13 min read