Embedding 安定化で検索リランキングのCold start problemを解決:LINEバイトでの適用事例紹介
LINEヤフーの技術カンファレンス「Tech-Verse 2026」の公式記事です。こんにちは。LINEヤフーで機械学習プラットフォームを開発している木原健太と袁逸凡です。今回は、LINEバイトの検索...
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LINEヤフーの技術カンファレンス「Tech-Verse 2026」の公式記事です。こんにちは。LINEヤフーで機械学習プラットフォームを開発している木原健太と袁逸凡です。今回は、LINEバイトの検索...
The idea that makes language models, recommendation systems, and semantic search actually workContinue reading on Medium »
Your social posts are in Gain, moving through approvals. But the landing page? You emailed the URL to your client and you’re waiting. The HTML banner? It’s in a Slack thread. The e...
We’ve all done it.Continue reading on Medium »
How a language model reads a word — and why context changes everythingContinue reading on Medium »
Modern semantic search, retrieval-augmented generation (RAG) pipelines, and large-scale recommendation models heavily rely on embeddings — transformations of natural language text...
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