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README.md

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 # From Text Segmentation to Smart Chaptering: A Novel Benchmark for Structuring Video Transcriptions
 
-We present <span style="font-variant:small-caps; font-weight:700;">YTSeg</span>, a topically and structurally diverse benchmark for the text segmentation task based on YouTube transcriptions. The dataset comprises 19,299 videos from 393 channels, amounting to 6,533 content hours. The topics are wide-ranging, covering domains such as science, lifestyle, politics, health, economy, and technology. The videos are from various types of content formats, such as podcasts, lectures, news, corporate events \& promotional content, and, more broadly, videos from individual content creators. We refer to the [paper](https://aclanthology.org/2024.eacl-long.25/) for further information.
+We present <span style="font-variant:small-caps; font-weight:700;">YTSeg</span>, a topically and structurally diverse benchmark for the text segmentation task based on YouTube transcriptions. The dataset comprises 19,299 videos from 393 channels, amounting to 6,533 content hours. The topics are wide-ranging, covering domains such as science, lifestyle, politics, health, economy, and technology. The videos are from various types of content formats, such as podcasts, lectures, news, corporate events \& promotional content, and, more broadly, videos from individual content creators. We refer to the **paper** ([acl](https://aclanthology.org/2024.eacl-long.25/) | [arXiv](https://arxiv.org/abs/2402.17633)) for further information.
 
 ## Data Overview