Update paper reference

README.md

@@ -14,7 +14,7 @@ size_categories:
 
 # 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://arxiv.org/abs/2402.17633) 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](https://aclanthology.org/2024.eacl-long.25/) for further information.
 
 ## Data Overview
 
@@ -85,14 +85,21 @@ test_data = get_title_partition('test')
 
 ## Citing
 
-We kindly request you to cite our corresponding paper (accepted to EACL 2024) if you use our dataset.
+We kindly request you to cite our corresponding EACL 2024 paper if you use our dataset.
 
 ```
-@article{retkowski2024ytseg,
-  title={From Text Segmentation to Smart Chaptering: A Novel Benchmark for Structuring Video Transcriptions},
-  author={Retkowski, Fabian and Waibel, Alexander},
-  journal={arXiv preprint arXiv:2402.17633},
-  year={2024}
+@inproceedings{retkowski-waibel-2024-text,
+    title = "From Text Segmentation to Smart Chaptering: A Novel Benchmark for Structuring Video Transcriptions",
+    author = "Retkowski, Fabian  and Waibel, Alexander",
+    editor = "Graham, Yvette  and Purver, Matthew",
+    booktitle = "Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)",
+    month = mar,
+    year = "2024",
+    address = "St. Julian{'}s, Malta",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2024.eacl-long.25",
+    pages = "406--419",
+    abstract = "Text segmentation is a fundamental task in natural language processing, where documents are split into contiguous sections. However, prior research in this area has been constrained by limited datasets, which are either small in scale, synthesized, or only contain well-structured documents. In this paper, we address these limitations by introducing a novel benchmark YTSeg focusing on spoken content that is inherently more unstructured and both topically and structurally diverse. As part of this work, we introduce an efficient hierarchical segmentation model MiniSeg, that outperforms state-of-the-art baselines. Lastly, we expand the notion of text segmentation to a more practical {``}smart chaptering{''} task that involves the segmentation of unstructured content, the generation of meaningful segment titles, and a potential real-time application of the models.",
 }
 ```