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Understand the key terms behind AI detection, content analysis, and natural language processing. Click any term to read its full definition with examples.
A tool that analyzes text to determine whether it was written by a human or generated by an artificial intelligence model.
Text, images, audio, or video created by artificial intelligence models such as GPT-4, Claude, or Midjourney, often indistinguishable from human-created content.
The process of modifying AI-generated text to make it sound more natural and human-written, often to pass AI detection tools.
The degree to which a piece of content is unique and not derived from existing published sources, measured by plagiarism and AI detection tools.
When an AI detector incorrectly classifies human-written text as AI-generated, potentially causing unfair consequences for the author.
A readability formula that estimates the US school grade level required to understand a text, based on average sentence length and syllables per word.
Rewriting text to express the same meaning using different words and sentence structures, while maintaining the original intent.
A measurement of how surprised a language model is by a text. Lower perplexity suggests AI-generated content; higher perplexity suggests human writing.
The process of identifying text that has been copied from existing sources without proper attribution, using database comparison and fingerprinting algorithms.
The practice of designing and optimizing input prompts to get the best possible output from AI language models.
The process of condensing a longer text into a shorter version while retaining the key information and main ideas.
A neural network architecture that uses self-attention mechanisms to process sequential data in parallel, forming the foundation of all modern LLMs.