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pro vyhledávání: '"Kanumolu, Gopichand"'
TeClass: A Human-Annotated Relevance-based Headline Classification and Generation Dataset for Telugu
News headline generation is a crucial task in increasing productivity for both the readers and producers of news. This task can easily be aided by automated News headline-generation models. However, the presence of irrelevant headlines in scraped new
Externí odkaz:
http://arxiv.org/abs/2404.11349
Autor:
Ousidhoum, Nedjma, Muhammad, Shamsuddeen Hassan, Abdalla, Mohamed, Abdulmumin, Idris, Ahmad, Ibrahim Said, Ahuja, Sanchit, Aji, Alham Fikri, Araujo, Vladimir, Ayele, Abinew Ali, Baswani, Pavan, Beloucif, Meriem, Biemann, Chris, Bourhim, Sofia, De Kock, Christine, Dekebo, Genet Shanko, Hourrane, Oumaima, Kanumolu, Gopichand, Madasu, Lokesh, Rutunda, Samuel, Shrivastava, Manish, Solorio, Thamar, Surange, Nirmal, Tilaye, Hailegnaw Getaneh, Vishnubhotla, Krishnapriya, Winata, Genta, Yimam, Seid Muhie, Mohammad, Saif M.
Exploring and quantifying semantic relatedness is central to representing language and holds significant implications across various NLP tasks. While earlier NLP research primarily focused on semantic similarity, often within the English language con
Externí odkaz:
http://arxiv.org/abs/2402.08638
Fluency is a crucial goal of all Natural Language Generation (NLG) systems. Widely used automatic evaluation metrics fall short in capturing the fluency of machine-generated text. Assessing the fluency of NLG systems poses a challenge since these mod
Externí odkaz:
http://arxiv.org/abs/2312.01500