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Emotional RAG: Enhancing Role-Playing Intelligence through Emotional Retrieval - Chief AI Sharing Circle

Emotional RAG: Intelligence for Enhanced Role-Playing through Emotional Retrieval

Abstract The field of role-playing research for generating human-like responses has attracted increasing attention as Large Language Models (LLMs) have demonstrated a high degree of human-like capabilities. This has facilitated the exploration of role-playing agents in a variety of applications, such as chatbots that can engage in natural conversations with users, and those that can provide personalized...

AI Engineering Academy: 2.7 ReRanker RAG (Reordering) - Chief AI Sharing Circle

AI Engineering Academy: 2.7 ReRanker RAG (Reordering)

The reordering model will improve the results of semantic ranking by reordering the list of candidate documents based on their semantic match to the user's question. Commonly used bge-reranker-v2-m3 or cohere

AI education track 10,000 words analysis: what are the representative products? What are the opportunities? What are the future possibilities? -Chief AI Sharing Circle

AI education track 10,000 words analysis: what are the representative products? What are the opportunities? What are the future possibilities?

Education has long been considered one of the industries that will be changed the most by LLM. education makes up a large portion of ChatGPT's usage scenarios, and its usage often fluctuates with the start of the school year and the regularity of vacations. Andrej Karpathy has chosen education as the direction of his venture. People are expecting to have all-round AI Tutor,...

AI Engineering Academy: 2.8 Hybrid RAG (same as 2.9) - Chief AI Sharing Circle

AI Engineering College: 2.8 mixed RAG (same as 2.9)

Sentence-Window-Based Retriever RAG Approach Introduction The Sentence-Window-Based Retriever RAG (Retrieval-Augmented Generation) approach is a high-level implementation of the RAG framework designed to enhance the context-awareness and coherence of AI-generated responses. The approach combines a large-scale language model with a high ...

Featured Model Context Protocol (MCP) Server List (Updated)

What is MCP: Anthropic's open source Model Context Protocol: Model Context Protocol (MCP), which gives AI assistants native access to local data Reference Implementation Server Filesystem - Provides secure file manipulation and supports configurable access control GitHub - Repository management, file...

AI Engineering Academy: 2.10 Auto Merge Retriever - Chief AI Sharing Circle

AI Engineering Academy: 2.10 Automated Merge Retriever

Introduction The Automated Merge Retriever is a high-level implementation of the Enhanced Retrieval Generation (RAG) framework. It aims to enhance the context-awareness and coherence of AI-generated responses by merging potentially fragmented and smaller contexts into larger and more comprehensive ones. https://github.com/adith...

Complex Reasoning Capabilities of Large Models from OpenAI-o1 - Chief AI Sharing Circle

Complex Reasoning for Large Models from OpenAI-o1

In 2022 OpenAI released ChatGPT, which became the world's fastest APP to break through the hundreds of millions of users, and at that time people thought that we were closer to true artificial intelligence. But people soon realized that ChatGPT could talk and chat, and even write poems and articles, but it still wasn't quite as good at simple logic...

Learn TOML format profile in a minute - Chief AI Sharing Circle

Learn TOML format configuration files in a minute

TOML is a clean and simple configuration file format 📄 designed to be more human readable and writable ✨. ✅ Easier to write: Configurations are represented as key-value pairs without complex indentation and syntax rules, reducing the error rate. ✅ Clearer: Supports grouping and nesting structure, clear hierarchy, configuration logic...

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