# KNOWLEDGE

- [Vector Databases](/knowledge/vector-databases.md)
- [A Comprehensive Survey on Vector Databases](/knowledge/vector-databases/a-comprehensive-survey-on-vector-databases.md)
- [Vector database management systems: Fundamental concepts, use-cases, and current challenges](/knowledge/vector-databases/vector-database-management-systems-fundamental-concepts-use-cases-and-current-challenges.md)
- [Using the Output Embedding to Improve Language Models](/knowledge/vector-databases/using-the-output-embedding-to-improve-language-models.md)
- [Decoding Sentence-BERT](/knowledge/vector-databases/decoding-sentence-bert.md)
- [ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT](/knowledge/vector-databases/colbert-efficient-and-effective-passage-search-via-contextualized-late-interaction-over-bert.md): The widely cited paper by Omar Khattab and Matei Zaharia from Stanford University
- [SimCSE: Simple Contrastive Learning of Sentence Embeddings](/knowledge/vector-databases/simcse-simple-contrastive-learning-of-sentence-embeddings.md)
- [Questions Are All You Need to Train a Dense Passage Retriever](/knowledge/vector-databases/questions-are-all-you-need-to-train-a-dense-passage-retriever.md)
- [Improving Text Embeddings with Large Language Models](/knowledge/vector-databases/improving-text-embeddings-with-large-language-models.md): Microsoft Corporation
- [Massive Text Embedding Benchmark](/knowledge/vector-databases/massive-text-embedding-benchmark.md): The leaderboard for embedding models
- [RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking](/knowledge/vector-databases/rocketqav2-a-joint-training-method-for-dense-passage-retrieval-and-passage-re-ranking.md)
- [LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders](/knowledge/vector-databases/llm2vec-large-language-models-are-secretly-powerful-text-encoders.md)
- [Embedding and Fine-Tuning in Neural Language Models](/knowledge/vector-databases/embedding-and-fine-tuning-in-neural-language-models.md): Mathematical representations of text
- [Embedding Model Construction](/knowledge/vector-databases/embedding-model-construction.md)
- [Demystifying Embedding Spaces using Large Language Models](/knowledge/vector-databases/demystifying-embedding-spaces-using-large-language-models.md): Guy Tennenholtz et al. from Google Research
- [Fine-Tuning Llama for Multi-Stage Text Retrieval](/knowledge/vector-databases/fine-tuning-llama-for-multi-stage-text-retrieval.md): Microsoft Research
- [Large Language Model Based Text Augmentation Enhanced Personality Detection Model](/knowledge/vector-databases/large-language-model-based-text-augmentation-enhanced-personality-detection-model.md)
- [One Embedder, Any Task: Instruction-Finetuned Text Embeddings](/knowledge/vector-databases/one-embedder-any-task-instruction-finetuned-text-embeddings.md)
- [Vector Databases are not the only solution](/knowledge/vector-databases/vector-databases-are-not-the-only-solution.md): Yingjun Wu
- [Knowledge Graphs](/knowledge/vector-databases/knowledge-graphs.md): Analysis of Knowledge Graphs and Influence of Generative AI and LLMs
- [Harnessing Knowledge Graphs to Elevate AI: A Technical Exploration](/knowledge/vector-databases/knowledge-graphs/harnessing-knowledge-graphs-to-elevate-ai-a-technical-exploration.md): Finally a semantic data architecture
- [Unifying Large Language Models and Knowledge Graphs: A Roadmap](/knowledge/vector-databases/knowledge-graphs/unifying-large-language-models-and-knowledge-graphs-a-roadmap.md)
- [Approximate Nearest Neighbor (ANN)](/knowledge/vector-databases/approximate-nearest-neighbor-ann.md)
- [High Dimensional Data](/knowledge/vector-databases/high-dimensional-data.md)
- [Principal Component Analysis (PCA)](/knowledge/vector-databases/principal-component-analysis-pca.md)
- [Vector Similarity Search - HNSW](/knowledge/vector-databases/vector-similarity-search-hnsw.md)
- [FAISS (Facebook AI Similarity Search)](/knowledge/vector-databases/faiss-facebook-ai-similarity-search.md)
- [Unsupervised Dense Retrievers](/knowledge/vector-databases/unsupervised-dense-retrievers.md)
- [Retrieval Augmented Generation](/knowledge/retrieval-augmented-generation.md): A critical piece of the generative AI infrastructure
- [Retrieval-Augmented Generation for Large Language Models: A Survey](/knowledge/retrieval-augmented-generation/retrieval-augmented-generation-for-large-language-models-a-survey.md)
- [Fine-Tuning or Retrieval?](/knowledge/retrieval-augmented-generation/fine-tuning-or-retrieval.md): Microsoft, Israel
- [Revolutionising Information Retrieval: The Power of RAG in Language Models](/knowledge/retrieval-augmented-generation/revolutionising-information-retrieval-the-power-of-rag-in-language-models.md)
- [A Survey on Retrieval-Augmented Text Generation](/knowledge/retrieval-augmented-generation/a-survey-on-retrieval-augmented-text-generation.md): Huayang Li, Yixuan Su, Deng Cai, Yan Wang, Lemao Liu
- [REALM: Retrieval-Augmented Language Model Pre-Training](/knowledge/retrieval-augmented-generation/realm-retrieval-augmented-language-model-pre-training.md): Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, Ming-Wei Chang
- [Retrieve Anything To Augment Large Language Models](/knowledge/retrieval-augmented-generation/retrieve-anything-to-augment-large-language-models.md)
- [Generate Rather Than Retrieve: Large Language Models Are Strong Context Generators](/knowledge/retrieval-augmented-generation/generate-rather-than-retrieve-large-language-models-are-strong-context-generators.md)
- [Active Retrieval Augmented Generation](/knowledge/retrieval-augmented-generation/active-retrieval-augmented-generation.md): FLARE!
- [DSPy: LM Assertions: Enhancing Language Model Pipelines with Computational Constraints](/knowledge/retrieval-augmented-generation/dspy-lm-assertions-enhancing-language-model-pipelines-with-computational-constraints.md)
- [DSPy: Compiling Declarative Language Model Calls](/knowledge/retrieval-augmented-generation/dspy-compiling-declarative-language-model-calls.md)
- [DSPy: In-Context Learning for Extreme Multi-Label Classification](/knowledge/retrieval-augmented-generation/dspy-in-context-learning-for-extreme-multi-label-classification.md)
- [Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs](/knowledge/retrieval-augmented-generation/optimizing-instructions-and-demonstrations-for-multi-stage-language-model-programs.md)
- [HYDE: Revolutionising Search with Hypothetical Document Embeddings](/knowledge/retrieval-augmented-generation/hyde-revolutionising-search-with-hypothetical-document-embeddings.md)
- [Enhancing Recommender Systems with Large Language Model Reasoning Graphs](/knowledge/retrieval-augmented-generation/enhancing-recommender-systems-with-large-language-model-reasoning-graphs.md)
- [Retrieval Augmented Generation (RAG) versus fine tuning](/knowledge/retrieval-augmented-generation/retrieval-augmented-generation-rag-versus-fine-tuning.md)
- [RAFT: Adapting Language Model to Domain Specific RAG](/knowledge/retrieval-augmented-generation/raft-adapting-language-model-to-domain-specific-rag.md)
- [Summarisation Methods and RAG](/knowledge/retrieval-augmented-generation/summarisation-methods-and-rag.md)
- [Lessons Learned on LLM RAG Solutions](/knowledge/retrieval-augmented-generation/lessons-learned-on-llm-rag-solutions.md): Injecting data via embedding model into your vector database for future retrieval
- [Stanford: Retrieval Augmented Language Models](/knowledge/retrieval-augmented-generation/stanford-retrieval-augmented-language-models.md): Youtube Lecture - January 2024
- [Overview of RAG Approaches with Vector Databases](/knowledge/retrieval-augmented-generation/overview-of-rag-approaches-with-vector-databases.md): Some random tips on RAG and vector databases
- [Mastering Chunking in Retrieval-Augmented Generation (RAG) Systems](/knowledge/retrieval-augmented-generation/mastering-chunking-in-retrieval-augmented-generation-rag-systems.md)
- [Semantic Routing](/knowledge/semantic-routing.md)
- [Resource Description Framework (RDF)](/knowledge/resource-description-framework-rdf.md)