This paper presents a novel approach for solving the Complex Word Identification (CWI) task using the text-to-text generative model. The CWI task involves identifying complex words in text, which is a challenging Natural Language Processing task. ...

• The paper proposes a transformer based generative approach for complex word identification (CWI)
• Our technique uses text generation and addresses the CWI task in the text-to-text context.
• The paper also proposes and develops a new ...

Diffusion models have revolted the field of text-to-image generation recently. The unique way of fusing text and image information contributes to their remarkable capability of generating highly text-related images. From another perspective, ...

• A novel plug-and-play method for open-vocabulary segmentation is proposed.
• A new benchmark named “personalized referring image segmentation” is introduced.
• Our framework achieves state-of-the-art performance on several segmentation ...

The enormous quantity of text makes it challenging for users to obtain the key information and knowledge. Automatic text summarization can alleviate this problem by providing reliable summaries for massive text documents. During the last decade, ...

• Significant achievements of automatic text summarization have been made.
• We aim to explore the research community of automatic text summarization.
• Incorporating with NLP, text summarization applied knowledge-based, graph-based and ...

Specifically focusing on the landscape of abstractive text summarization, as opposed to extractive techniques, this survey presents a comprehensive overview, delving into state-of-the-art techniques, prevailing challenges, and prospective ...

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• Overview of state-of-the-art techniques in abstractive text summarization.
• Comparative analysis of models in abstractive summarization.
• Identification of challenges and potential improvements in the field.
• Exploration of future ...