Surya Maddulasuryamaddula.com·Sep 23, 2024Not RAG, but RAG Fusion? Understanding Next-Gen Info Retrieval.Not RAG, but RAG Fusion? Understanding Next-Gen Info Retrieval. AI and Natural Language Processing are advancing at an incredible pace, and now more than ever, we need better and more RELIABLE ways to find and use information. As we've all experienc...10 likes·188 readsinformation retrival
AASHIFaashif.hashnode.dev·Jun 24, 2024UDA - Unstructured Document AnalysisUDA: A Benchmark Suite for Retrieval-Augmented Generation in Real-world Document Analysis Introduction In recent years, the use of Retrieval-Augmented Generation (RAG) has significantly enhanced the capabilities of Large Language Models (LLMs), enabl...Information Retrieval
Mishika Shahtechnoo.hashnode.dev·May 16, 2024Summarization Superpower: How Automatic Tools Can Help You Conquer Text MountainsWhat is text Summarization exactly? Text summarization is the process of distilling the key points of a text document into a shorter version while preserving the most important information. It's a crucial task in natural language processing (NLP) and...1 likeArtificial Intelligence
Farhan Naqvifarhanbytemaster.hashnode.dev·Apr 2, 2024How context window of LLMS cause hindrance in RAG appsA comprehensive overview of the challenges posed by restricted context windows in Retrieval-Augmented Generation (RAG) apps:. Token Limit and Context window in RAG: Large Language Models (LLMs): RAG models often rely on pre-trained LLMs for the gene...AI
Farhan Naqvifarhanbytemaster.hashnode.dev·Mar 30, 2024Issues with RAG applicationsRetrieval-Augmented Generation (RAG) is a powerful technique, but it does come with some challenges: Finding Relevant Documents: The retrieval process is crucial, as RAG relies on identifying relevant documents to inform the generation process. If t...AI
Farhan Naqvifarhanbytemaster.hashnode.dev·Mar 28, 2024Components of a RAG ApplicationRAG (Retrieval-Augmented Generation) includes three main components: Embedding Model: This model takes textual information (queries, documents, etc.) and transforms them into numerical representations called "embeddings." These embeddings capture th...generative ai
Rohit Mehrareco.hashnode.dev·Feb 9, 2024Popularity Bias in Recommender SystemsPopular items are recommended even more frequently than their popularity would warrant The long-tail phenomenon is common in RS data: in most cases, a small fraction of popular items account for most user interactions When trained on such long-tail...recsys
Jessica Anna Jamesjessica1438.hashnode.dev·Feb 5, 2024From Voice to Insight: The Journey of Speech Data Retrieval using NLP technologyIn the fast-paced digital era, information is power. But the real challenge lies not just in accessing information, but in efficiently retrieving and processing it, especially when it comes from diverse sources like speech. Speech data, abundant in o...37 readsnlp
Manik Khandelwalsoftware-engineering.hashnode.dev·Dec 27, 2023Retrieval augmented version of LLMA retrieval-augmented version of a large language model (LLM) is a type of LLM that utilizes an information retrieval (IR) system to enhance its performance. Imagine it like this: the LLM is a powerful engine, but it needs the right fuel and guidance...information retrival
picipici.hashnode.dev·Oct 31, 2023Word embeddingIntroduction Word embeddings have become a foundational technology in Natural Language Processing (NLP), providing a way to represent words and documents in a numerical format. In this blog post, we'll explore the use of word embeddings in the contex...Natural Language Processingnlp
