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TeClass: A Human-Annotated Relevance-based Headline Classification and Generation Dataset for Telugu
April 18, 2024, 4:47 a.m. | Gopichand Kanumolu, Lokesh Madasu, Nirmal Surange, Manish Shrivastava
cs.CL updates on arXiv.org arxiv.org
Abstract: 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 news articles results in sub-optimal performance of generation models. We propose that relevance-based headline classification can greatly aid the task of generating relevant headlines. Relevance-based headline classification involves categorizing news headlines based on their relevance to the corresponding …
abstract articles arxiv automated classification cs.cl dataset however human performance productivity readers results telugu type
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