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Thankfully, researchers at the Allen Institute for Artificial Intelligence have developed a new model to summarize text from scientific papers, and present it in a few sentences in the form of TL ...
Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.
Even though the AI is conservative at removing information and details, the text's length usually decrease by quite a bit as it removes redundant phrases. The AI is also good at reordering phrases to make the text more coherent, but at the cost of grammar errors and obscuring meaning.
Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. The resulting summary report allows individual users, such as professional information consumers, to quickly familiarize themselves with information contained in a large cluster of documents.
LangChain was launched in October 2022 as an open source project by Harrison Chase, while working at machine learning startup Robust Intelligence. The project quickly garnered popularity, [3] with improvements from hundreds of contributors on GitHub, trending discussions on Twitter, lively activity on the project's Discord server, many YouTube tutorials, and meetups in San Francisco and London.
Tag articles with appropriate templates, remove unsourced information and warn users who add unsourced AI-generated content to articles. Identifying AI-assisted edits is difficult in most cases since the generated text is often indistinguishable from human text. Some exceptions are if the text contains phrases like "as an AI model" or "as of my ...
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