Applications
QA (Question Answering)
Question answering systems take a natural language question and return an answer, either extracted from a provided context (extractive QA) or generated from the model's knowledge (generative QA). Benchmarks like SQuAD, TriviaQA, and Natural Questions have driven progress in this area.
Modern LLMs excel at open-domain generative QA, drawing on broad pre-trained knowledge. AI search products are essentially scaled QA systems that retrieve relevant passages before generating answers—making high-quality, question-answerable content a core GEO objective.
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Related Terms
Techniques & Methods
Retrieval Augmented Generation (RAG)
An inference-time architecture that retrieves relevant documents from a knowledge base or web index and injects them into a language model's context before generation, grounding answers in real source material.
Core Concepts
Natural Language Processing (NLP)
Field focused on enabling computer-human interaction through natural language.
Techniques & Methods
Extractive Summarization
Creating summaries by selecting and combining key sentences directly from the source text.
Applications
Dialogue System
AI system designed to carry on natural, coherent conversations with human users.