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...DiscussAI
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...DiscussAI
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...Discussgenerative ai
Rohit MehraforRecommender Systemsreco.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...Discussrecsys
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...Discuss·26 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...Discussinformation 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...DiscussNatural Language Processingnlp
Mundher Al-Shabi, PhDmundher.com·Oct 7, 2023Model-Based Retrieval SystemInformation retrieval aims to locate text-based information relevant to a query within a substantial pool of potential sources. In its early stages, sparse retrieval primarily emphasized term matching using sparse representations and inverted indexes...Discussllm
SubeeTalksallaboutai.hashnode.dev·Sep 27, 2023Researchers Introduce RankVicuna, An Open-Source Model Elevating Zero-Shot Reranking in Information RetrievalIn the realm of information retrieval, the limitations and proprietary nature of Large Language Models (LLMs) like GPT have posed significant challenges in terms of reproducibility and reliability, restricting extensive applications and experiments. ...Discussllm
Rohit MehraforRecommender Systemsreco.hashnode.dev·Sep 7, 2023"Simplicity and Effectiveness: Unveiling EASE for Recommendation Systems"In the world of recommendation systems, the quest for simplicity often leads to remarkable breakthroughs. The "Embarrassingly Shallow Autoencoders for Sparse Data," or EASE, is one such breakthrough that combines simplicity with state-of-the-art perf...Discussrecommendations
