h4cker/ai_research/RAG

RAG Resources

• Files from my "Using Retrieval Augmented Generation (RAG), Langchain, and LLMs for Cybersecurity Operations" Course
• LangFlow - a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database.

Disadvantages of RAG

• Disadvantages of RAG

RAG Patterns

• Generative AI Lifecycle Patterns
• Why do RAG pipelines fail? Advanced RAG Patterns — Part1 Ozgur Guler
• How to improve RAG peformance — Advanced RAG Patterns — Part2
• Patterns for Building LLM-based Systems & Products
• AI Engineer Summit - Building Blocks for LLM Systems & Products
• Technical Considerations for Complex RAG

Dialogue Routing

• Routing in RAG-Driven Applications

Retrieval

Vector Retrieval

• Boosting RAG: Picking the Best Embedding & Reranker models
• What We Need to Know Before Adopting a Vector Database

Chunking

• Chunking Strategies for LLM Applications
• Evaluating the Ideal Chunk Size for a RAG System using LlamaIndex
• How to Chunk Text Data — A Comparative Analysis

Embeddings

Vector Search

• Awesome Search
• Advanced RAG Retrieval Strategies: Sentence Window Retrieval

Not Vector Retrieval

• Vector Search Is Not All You Need
• Build a search engine, not a vector DB
• Improving RAG (Retrieval Augmented Generation) Answer Quality with Re-ranker
• From Search to Synthesis: Enhancing RAG with BM25 and Reciprocal Rank Fusion

Generation

Prompts

• Emerging RAG & Prompt Engineering Architectures for LLMs
• How to Cut RAG Costs by 80% Using Prompt Compression

Prompting strategies

Multi-Modal RAG

• Multi-Modal RAG

Multi-index RAG

• Having all of your data stored in one collection isn't always the best for RAG apps

Multi-Document

• Advanced RAG — Multi-Documents Agent with LlamaIndex

FLARE

• Better RAG with Active Retrieval Augmented Generation FLARE

Chain-of-Verification

• in-Of-Verification Reduces Hallucination in LLMs

Chain-Of-Thought

• Chain-Of-Thought Prompting In LLMs

Context

• The Needle In a Haystack Test
• Conversational Memory for LLMs with Langchain

Long context RAG

• The next generation of RAG: Long-Context RAG
• NVIDIA Research: RAG with Long Context LLMs

Knowledge and Knowledge Graphs

• Graph RAG: Unleashing the Power of Knowledge Graphs with LLM

• Embeddings + Knowledge Graphs: The Ultimate Tools for RAG Systems

• The Practical Benefits to Grounding an LLM in a Knowledge Graph Daniel Bukowski

• Implement RAG with Knowledge Graph and Llama-Index

• Awesome Knowledge Graphs

• HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models

Automated prompt optimization

Hallucination

• How to Detect Hallucinations in LLMs
• Measuring Hallucinations in RAG Systems

Guardrails

• Safeguarding LLMs with Guardrails
• NeMo Guardrails: The Missing Manual

LLM Models

Finetuning and Pretraining

• Fine-Tuning Llama 2.0 with Single GPU Magic
• Practitioners guide to fine-tune LLMs for domain-specific use case
• Are You Pre-training your RAG Models on Your Raw Text?
• Combine Multiple LoRA Adapters for Llama 2
• RAG vs Finetuning — Which Is the Best Tool to Boost Your LLM Application?

Evaluation of RAGs

• RAG Evaluation
• Evaluating RAG: A journey through metrics
• Exploring End-to-End Evaluation of RAG Pipelines
• Evaluation Driven Development, the Swiss Army Knife for RAG Pipelines
• Evaluating the Ideal Chunk Size for a RAG System using LlamaIndex

Performance and cost

• Secrets to Optimizing RAG LLM Apps for Better Performance, Accuracy and Lower Costs!

Privacy

• Masking PII Data in RAG Pipeline

Security

• Hijacking Chatbots: Dangerous Methods Manipulating GPTs

Applications of RAG

Chatbots

Tools

• Three Open-Source RAG Tools You Need to Know About
• HayStack
• RAGAS

DSPy

• DSPy — Does It Live Up To The Hype?

AutoRAG

• AutoRAG - AutoML tool for RAG. Automatically optimize RAG pipeline with single YAML file.

AutoGPT

Langchain

• Langchain
• Langchain is NOT for production use. Here is why ..

LlamaIndex

• LlamaIndex

• Building Production-Ready LLM Apps with LlamaIndex: Document Metadata for Higher Accuracy Retrieval

• Building Production-Ready LLM Apps With LlamaIndex: Recursive Document Agents for Dynamic Retrieval

Vendor-specific examples

• RAG Pipeline with Mistral 7B Instruct Model in Colab: A Step-by-Step Guide Qendel AI GoPenAI

Elastcisearch + OpenAI

• ChatGPT and Elasticsearch: OpenAI meets private data

OpenAI and ChatGPT

• Compare PDF Question Answering Systems Build with OpenAI and Google VertexAI

Tools and fucntions

• Unlocking the Power of the OpenAI API: Master Function-Calling with Practical Examples
• penAI/Chat-GPT Function Calling : for Enhanced AI Interactions

Vespa

• Hands-On RAG guide for personal data with Vespa and LLamaIndex

Qdrant

Running RAGs in production

Vectors corner

• Similarity Search, Part 2: Product Quantization
• Binary and Scalar Embedding Quantization for Significantly Faster & Cheaper Retrieval
• Cohere int8 & binary Embeddings - Scale Your Vector Database to Large Datasets Image of Nils Reimers

Research Papers

Survey and Benchmark

Benchmarking Large Language Models in Retrieval-Augmented Generation
Jiawei Chen, Hongyu Lin, Xianpei Han, Le Sun
arXiv 2023. [Paper][Github]
4 Sep 2023

Retrieval-enhanced LLMs

Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models
Wenhao Yu, Hongming Zhang, Xiaoman Pan, Kaixin Ma, Hongwei Wang, Dong Yu
arxiv - Nov 2023 [Paper]

REST: Retrieval-Based Speculative Decoding
Zhenyu He, Zexuan Zhong, Tianle Cai, Jason D Lee, Di He
arXiv - Nov 2023 [Paper][Github]

Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
Anonymous
ICLR 24 – Oct 2023 [paper]

Self-Knowledge Guided Retrieval Augmentation for Large Language Models
Yile Wang, Peng Li, Maosong Sun, Yang Liu
arXiv - Oct 2023 [Ppaer]

Retrieval meets Long Context Large Language Models
Peng Xu, Wei Ping, Xianchao Wu, Lawrence McAfee, Chen Zhu, Zihan Liu, Sandeep Subramanian, Evelina Bakhturina, Mohammad Shoeybi, Bryan Catanzaro
arxiv - Oct 2023 [Paper]

DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T. Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, Christopher Potts
arXiv – Oct 2023 [paper] [code]

Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts
Jian Xie, Kai Zhang, Jiangjie Chen, Renze Lou, Yu Su
ICLR 24 – May 2023 [paper] [code]

Active Retrieval Augmented Generation
Zhengbao Jiang, Frank F. Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, Graham Neubig
arXiv – May 2023 [paper] [code]

REPLUG: Retrieval-Augmented Black-Box Language Models
Weijia Shi, Sewon Min, Michihiro Yasunaga, Minjoon Seo, Rich James, Mike Lewis, Luke Zettlemoyer, Wen-tau Yih
arXiv – Jan 2023 [paper]

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, Douwe Kiela NeurIPS 2020 - May 2020 [Paper]

RAG Instruction Tuning

RA-DIT: Retrieval-Augmented Dual Instruction Tuning
Anonymous
ICLR 24 – Oct 23 [paper]

InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining
Boxin Wang, Wei Ping, Lawrence McAfee, Peng Xu, Bo Li, Mohammad Shoeybi, Bryan Catanzaro
arXiv - Oct 23 [paper]

RAG In-Context Learning

In-Context Retrieval-Augmented Language Models
Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
AI21 Labs – Jan 2023 [paper] [code]

RAG Embeddings

RegaVAE: A Retrieval-Augmented Gaussian Mixture Variational Auto-Encoder for Language Modeling
Jingcheng Deng, Liang Pang, Huawei Shen, Xueqi Cheng
EMNLP 2023 - Oct 2023 [Paper][Github]

Text Embeddings Reveal (Almost) As Much As Text
John X. Morris, Volodymyr Kuleshov, Vitaly Shmatikov, Alexander M. Rush
EMNLP 2023 - Oct 2023 [Paper][Github]

Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents
Michael Günther, Jackmin Ong, Isabelle Mohr, Alaeddine Abdessalem, Tanguy Abel, Mohammad Kalim Akram, Susana Guzman, Georgios Mastrapas, Saba Sturua, Bo Wang, Maximilian Werk, Nan Wang, Han Xiao
arXiv - Oct 2023. [Paper][Model]

RAG Simulators

KAUCUS: Knowledge Augmented User Simulators for Training Language Model Assistants
Kaustubh D. Dhole
Simulation of Conversational Intelligence in Chat, EACL 2024 [Paper]

RAG Search

RAG Long-text and Memory

HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models
Bernal Jiménez Gutiérrez, Yiheng Shu, Yu Gu, Michihiro Yasunaga, Yu Su
arXiv - May 2024 [paper] [GitHub]

Understanding Retrieval Augmentation for Long-Form Question Answering
Hung-Ting Chen, Fangyuan Xu, Shane A. Arora, Eunsol Choi
arXiv - Oct 2023 [Paper]

RAG Evaluation

ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems
Jon Saad-Falcon, Omar Khattab, Christopher Potts, Matei Zaharia
arXiv - Nov 2023. [Paper] [Github]

RAG Optimization

Learning to Filter Context for Retrieval-Augmented Generation
Zhiruo Wang, Jun Araki, Zhengbao Jiang, Md Rizwan Parvez, Graham Neubig
arxiv- Nov 2023 [Paper][Github]

Large Language Models Can Be Easily Distracted by Irrelevant Context
Freda Shi, Xinyun Chen, Kanishka Misra, Nathan Scales, David Dohan, Ed Chi, Nathanael Schärli, Denny Zhou
ICML 2023 - Jan 2023 [Paper][Github]

Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks
Akari Asai, Matt Gardner, Hannaneh Hajishirzi
NAACL 2022 - Dec 2021 [Paper][Github]

When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories
Alex Mallen, Akari Asai, Victor Zhong, Rajarshi Das, Daniel Khashabi, Hannaneh Hajishirzi
ACL 2023 - Dec 2022 [Paper][Github]

RAG Application

Deficiency of Large Language Models in Finance: An Empirical Examination of Hallucination
Haoqiang Kang, Xiao-Yang Liu
arXiv - Nov 2023 [Paper]

Clinfo.ai: An Open-Source Retrieval-Augmented Large Language Model System for Answering Medical Questions using Scientific Literature
Alejandro Lozano, Scott L Fleming, Chia-Chun Chiang, Nigam Shah
arXiv - Oct 2023. [Paper]

PEARL: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrievers
Sheshera Mysore, Zhuoran Lu, Mengting Wan, Longqi Yang, Steve Menezes, Tina Baghaee, Emmanuel Barajas Gonzalez, Jennifer Neville, Tara Safavi
arXiv - Nov 2023. [Paper]