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multi-hop-question-answering

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Wikipedia

KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.

knowledge-graph large-language-model logical-reasoning multi-hop-question-answering trustfulness

Python

6528

453

1 天前

sachink1729 / DSPy-Multi-Hop-Chain-of-Thought-RAG

Discover advanced AI techniques in my repository combining Multi-Hop Chain of Thought (CoT) and Retrieval-Augmented Generation (RAG) using DSPy and Indexify. Enhance complex problem-solving with multi-step reasoning and external knowledge integration. Perfect for AI enthusiasts and researchers.

人工智能聊天机器人机器学习 multi-hop-question-answering openaiapi rag retrieval-augmented-generation

Jupyter Notebook

9 个月前

anirbanbasu / dqa

Language models attempting multi-hop question answering (MHQA)

人工智能 large-language-models llms questions-and-answers generative-ai generative-ai-tools multi-hop-question-answering agentic-ai agents dspy reinforcement-learning

Python

1 个月前

anirbanbasu / crux

Multi-hop question answering (MHQA) with complex retrieval augmented generation (RAG)

人工智能 large-language-models 大语言模型 multi-hop-question-answering rag retrieval-augmented-generation

5 天前

Fan-Luo / Doctoral_Dissertation

A doctoral dissertation titled "Towards the Advancement of Open-Domain Textual Question Answering Methods". The dissertation presents several innovative solutions aimed at addressing the challenges faced by ODQA systems and improving the performance.

active-learning explainability information-retrieval 自然语言处理 multi-hop-question-answering

2 年前