Tagged articles

ranking optimization

4 articles · Page 1 of 1

Jul 24, 2026 · Artificial Intelligence

UniNote: Unifying Multimodal Representation and Ranking in a Single Embedding Model

UniNote introduces a unified multimodal embedding model that combines representation learning and ranking optimization in a single forward pass, using a two‑stage SFT‑then‑RL training paradigm and Matryoshka Representation Learning to achieve competitive Item‑to‑Item retrieval performance while reducing latency.

Item2ItemMatryoshka Representation LearningSFT

0 likes · 12 min read

UniNote: Unifying Multimodal Representation and Ranking in a Single Embedding Model

Big Data and Microservices

Jul 2, 2026 · Industry Insights

How an SEO Article Skill Automates Keyword Placement and Search‑Engine‑Friendly Structure

The article dissects an SEO‑focused Skill that encodes keyword research, search‑intent mapping, and structural signals into a five‑step workflow, showing how systematic automation improves ranking, reduces manual effort, and avoids keyword‑stuffing pitfalls through concrete metrics and versioned refinements.

Content automationSEOkeyword placement

0 likes · 21 min read

How an SEO Article Skill Automates Keyword Placement and Search‑Engine‑Friendly Structure

Baidu Maps Tech Team

Apr 27, 2026 · Artificial Intelligence

How an End-to-End Geolocation Search System Bridges Recall and Ranking

This article details an end-to-end geolocation search solution that unifies pre‑training, recall, and ranking with shared representations, knowledge distillation, and S2 spatial encoding to handle massive POI data, multi‑factor relevance, and real‑time response constraints.

S2 geometryend-to-end retrievalgeolocation search

0 likes · 20 min read

How an End-to-End Geolocation Search System Bridges Recall and Ranking

Machine Heart

Apr 2, 2026 · Artificial Intelligence

From Tokens to Revenue: Kuaishou’s GR4AD Pioneers Full‑Stack Generative Recommendation for Ads

GR4AD, Kuaishou’s generative recommendation system, redesigns the entire ad pipeline—from tokenizing multimodal ad material to value‑aware learning, lazy decoding, and dynamic beam search—delivering over 4 % revenue lift, higher eCPM, and sub‑100 ms latency for more than 400 million users.

AdvertisingGenerative RecommendationReal-time inference

0 likes · 17 min read

From Tokens to Revenue: Kuaishou’s GR4AD Pioneers Full‑Stack Generative Recommendation for Ads