Microsoft

RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture

There are two common ways in which developers are incorporating proprietary and domain-specific data when building applications of Large Language Models (LLMs): Retrieval-Augmented Generation (RAG) ...
GitHub

PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation

In recent years, Retrieval Augmented Generation (RAG) systems have made significant progress in extending the capabilities of Large Language Models (LLM) through external retrieval. However, these ...
GitHub

PA-RAG: RAG Alignment via Multi-Perspective Preference Optimization

https://drive.google.com/file/d/1g3tCcWhAOTzGwldLOjCvtwJ_4YaIK-rj/view?usp=drive_link. The qustions are sourced from the test split from ASQA, WebQustions, Natural ...
IEEE

Agentic RAG with Human-in-the-Retrieval

Abstract: Retrieval-Augmented Generation (RAG) has emerged as a promising solution to address key challenges faced by GenAI, such as hallucination, outdated or non-removable parametric knowledge, and ...