mlsanityData to 14 Oct 2026

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

arXiv 2403.08103 ↗First posted 12 Mar 2024cs.CL cs.AIcited by 0

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Abstract (arXiv)

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 .

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 3 references that are in the map. First posted on arXiv 12 Mar 2024.

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References · 2

  1. 2017Attention Is All You Needcited by 60,361
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599

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