Retrieval Augmented Generation: Streamlining the creation of intelligent natural language processing models

Retrieval Augmented Generation: Streamlining the creation of intelligent natural language processing models Teaching computers to understand how humans write and speak, known as natural language processing (NLP), is one of the oldest challenges in AI research. There has been a marked change in approach over the past two years, however. Where research once focused on developing specific frameworks

[Ryobot]

質問と取得ドキュメントのペア (複数) から個別に生成し，タイムステップ毎に生起確率を合算する手法late fusionは異なるモデルでアンサンブルしてるみたいで面白いね．バックワードして学習できる

[kiririmode]

RAGのメリットは言語モデル自体に新しい知識を再学習させることなく新しい知識を入れて回答を生成できるようにすること。