Methods We extracted and clustered text fragments from the titles and abstracts of 2 512 445 publications using artificial intelligence techniques, including natural language processing ... noun ...

With the continuous development of natural language processing (NLP) technology, text classification tasks have been widely used in multiple application fields. However, obtaining labeled data is ...

Kimi K2 was trained on over 10 trillion tokens, using a broad and multilingual dataset that includes natural language text, programming code, instruction-tuned examples, and real-world conversations.

The categorization of text is an essential and pivotal step in the process of natural language understanding and processing. There are a lot of different approaches to solving the problem of ...

Google has introduced LangExtract, an open-source Python library designed to help developers extract structured information from unstructured text using large language models such as the Gemini ...

Advanced semantic text chunking with custom structural markers, whole-text coherence preservation, and flexible token management. Features async processing, LangChain integration, and dynamic drift ...

Basic-NLP-Tasks A collection of beginner-friendly NLP tasks including tokenization, stemming, lemmatization, and text classification.