What is Passage Retrieval?
A retrieval technique that identifies specific passages within documents to answer user queries effectively.
More about Passage Retrieval:
Passage Retrieval focuses on extracting the most relevant passages from documents rather than retrieving entire documents. This approach uses models like dense retrieval or contextual embeddings to match user queries to specific sections of text.
Passage retrieval is crucial for applications like question answering, where presenting concise and accurate information directly improves the user experience.
Frequently Asked Questions
Why is passage retrieval important in AI applications?
It provides more precise and relevant answers by focusing on specific sections of text, improving tasks like knowledge retrieval and open-domain question answering.
What technologies are commonly used for passage retrieval?
Technologies like dense retrieval and semantic search are integral to effective passage retrieval.
From the blog
Custom model training and fine-tuning for GPT-3.5 Turbo
Today OpenAI announced that businesses and developers can now fine-tune GPT-3.5 Turbo using their own data. Find out how you can create a custom tuned model trained on your own data.
Herman Schutte
Founder
Revolutionizing University Engagement with AI Chatbots: A Look at SiteSpeakAI
Explore how universities are leveraging AI chatbots to enhance student engagement and streamline administrative tasks. Discover SiteSpeakAI, a tool that trains chatbots on website content to answer visitor queries.
Herman Schutte
Founder