Contextual Clarity: Generating Sentences with Transformer Models using Context-Reverso Data

Autor: Musaev, Ruslan
Rok vydání: 2024
Předmět:
Druh dokumentu: Working Paper
Popis: In the age of information abundance, the ability to provide users with contextually relevant and concise information is crucial. Keyword in Context (KIC) generation is a task that plays a vital role in and generation applications, such as search engines, personal assistants, and content summarization. In this paper, we present a novel approach to generating unambiguous and brief sentence-contexts for given keywords using the T5 transformer model, leveraging data obtained from the Context-Reverso API. The code is available at https://github.com/Rusamus/word2context/tree/main .
Databáze: arXiv