unite

How to Build Reliable RAG: A Deep Dive into 7 Failure Points and Evaluation Frameworks

Retrieval-Augmented Generation (RAG) is critical for modern AI architecture, serving as an essential framework for building context-aware agents. But moving from a basic prototype to a ...
GitHub

FROAV_ A Framework for RAG Observation and Agent V.md

We present FROAV (Framework for RAG Observation and Agent Verification), an open-source research plat- form that democratizes LLM agent research by providing a plug-and-play architecture com- bining ...
GitHub

ET Markets AI Intelligence Platform

Empower retail investors in India with institutional-grade AI-driven market intelligence, making sophisticated financial analysis accessible, fast, and actionable. Build an integrated platform that ...
IEEE

Efficient Vector-Multiplicative Privacy-Preserving Retrieval-Augmented Generation for Large Language Models

Abstract: Retrieval-Augmented Generation (RAG) grounds large language models (LLMs) in external knowledge, yet it is faces a fundamental trade-off between knowledge confidentiality and retrieval ...
IEEE

SAGE: A Framework of Precise Retrieval for RAG

Abstract: Retrieval-augmented generation (RAG) has demonstrated significant proficiency in conducting question-answering (QA) tasks within a specified corpus. Nonetheless, numerous failure instances ...