PromptKG Family: a Gallery of Prompt Learning & KG-related research works, toolkits, and paper-list.

A code repository indexing tool to supercharge your LLM experience.

A curated list of retrieval-augmented generation (RAG) in large language models

an intro to retrieval augmented large language model

RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.

Visualization for a Retrieval-Augmented Generation (RAG) Assistant 🤖❤️📚

Harnessing the Memory Power of the Camelids

Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of the Langchain, OpenAI GPTs ,META LLAMA3 , Agents.

[CVPR 2024] Retrieval-Augmented Image Captioning with External Visual-Name Memory for Open-World Comprehension

The code for the paper "RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction" (WWW 24 short paper)

Piazza-Updater automates updates to a Weaviate database with real-time vectorial data. By continuously searching the internet and integrating with Verba repositories, it enhances retrieval-augmented generation (RAG) capabilities, keeping your applications informed and responsive.

Synthesizing realistic and diverse text-datasets from augmented LLMs

Diverse Demonstrations Improve In-context Compositional Generalization

[CCL 2023] Revisiting k-NN for Fine-tuning Pre-trained Language Models

Este projeto é um sistema baseado em RAG (Retrieval-Augmented Generation) para notícias financeiras.

Node.js example to convert XML emails into a RAG source using OpenAI embeddings.

Document Q/A Application, Wants to query research papers tons of them ?? why not ask the data itself. Let Workdesk AI do the harder part. and let you do the research

The code for the paper "RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction" (WWW'24, Short)

A multilingual Retrieval-Augmented Evaluation Pipeline for fact-checking and definition modeling with optional fact-splitting.

My bachelor's and master's theses