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Ele.me Technology

Apr 10, 2025 · Artificial Intelligence

Ele.me Vertical Business AIGC Image Model: Architecture, Training Pipeline, and Evaluation

Ele.me created a domain-specific AIGC image model built from scratch on its own data using the DiT backbone, a three-stage training pipeline (transformer pre-training, prompt alignment, aesthetic fine-tuning), custom T5‑E‑CLIP text and visual encoders, ControlNet for layout control, and evaluated via FID, CLIP scores and a human rubric, enabling automated dish-image generation and UI asset creation for its vertical business.

AIGCControlNetDiT

0 likes · 8 min read

Ele.me Vertical Business AIGC Image Model: Architecture, Training Pipeline, and Evaluation

DataFunTalk

Nov 7, 2018 · Artificial Intelligence

Evolution of Ele.me Recommendation Algorithms and Online Learning Practice

This article outlines the background of Ele.me's recommendation business, details the evolution of its recommendation algorithms from rule‑based models to deep learning and online learning, and explains the practical implementation of real‑time data pipelines, feature engineering, model training, and deployment.

Ele.meFeature Engineeringmachine learning

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Evolution of Ele.me Recommendation Algorithms and Online Learning Practice

DataFunTalk

Oct 12, 2018 · Artificial Intelligence

Market Mechanisms and Control Measures in Ele.me Food Delivery Recommendation Algorithms

The article presents a comprehensive overview of Ele.me's food‑delivery recommendation system, detailing its business model, platform goals, unique challenges, market‑driven efficiency mechanisms, control strategies, system architecture, model evolution, and online‑learning techniques used to balance short‑term performance with long‑term ecosystem health.

AIEle.meRanking

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Market Mechanisms and Control Measures in Ele.me Food Delivery Recommendation Algorithms

Ctrip Technology

Jan 4, 2018 · Artificial Intelligence

Intelligent Scheduling and Pressure‑Balancing System at Ele.me: Machine‑Learning Applications

This article introduces Ele.me's intelligent scheduling platform, focusing on the pressure‑balancing subsystem and demonstrating how machine‑learning models such as rider capacity estimation and team pressure‑coefficient prediction are designed, trained, and deployed to improve real‑time O2O delivery operations.

Ele.meLogisticsmachine learning

0 likes · 14 min read

Intelligent Scheduling and Pressure‑Balancing System at Ele.me: Machine‑Learning Applications

System Architect Go

May 8, 2017 · Frontend Development

Recap of Ele.me Frontend Technology Conference: PWA, Collaboration, Dependency Monitoring, Vue, Flow, and More

The author recounts attending Ele.me's front‑end technology conference, summarizing seven sessions covering PWA implementation, evolving front‑back collaboration, dependency health monitoring, Vue usage, Flow and type theory, design perspectives on Element, and the exploration of a visual document editor, while sharing personal impressions.

ConferenceEle.meFlow

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Recap of Ele.me Frontend Technology Conference: PWA, Collaboration, Dependency Monitoring, Vue, Flow, and More