Why send your data to the cloud when your PC can do it better?

Abstract: Abstractive text summarization uses the summarizer’s own words to capture the main information of a source document in a summary. While it is more challenging to automate than extractive ...

Many Qwen LLMs are among the most popular models on Hugging Face (Fig. 1). Qwen is continuously developing the models: after ...

All the benefits of plugins with none of the downsides.

The Claude API can automate customer support, document processing, and content workflows at scale. Here's how businesses are actually using it in 2026 — with real examples.

In this paper, we present approaches used in text summarization, showing how they can be adapted for speech summarization and where they fall short. Informal style and apparent lack of structure in ...

Phone scams aren’t the only threat anymore — scam text messages (also called “smishing”) are exploding in frequency and in financial damage. According to recent FTC data, Americans lost over $470 ...

Add a description, image, and links to the python-summarization-text-summarization topic page so that developers can more easily learn about it.

LangExtract lets users define custom extraction tasks using natural language instructions and high-quality “few-shot” examples. This empowers developers and analysts to specify exactly which entities, ...

LangGraph is a powerful framework by LangChain designed for creating stateful, multi-actor applications with LLMs. It provides the structure and tools needed to build sophisticated AI agents through a ...

Objective: This study aims to present the current state of the art on clinical text summarization using large language models, evaluate the level of evidence in existing research and assess the ...