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IEEE/ICACT20260145 Slide.12        [Big Slide]	Oral Presentation
	For evaluation, we selected two distinct datasets to test different aspects of our model.​ First, we used CNN/DailyMail. This is the standard benchmark for news summarization. Since news articles often have lead bias, we followed the standard practice of generating 3-sentence summaries to ensure a fair comparison with prior works.​ ​ However, to verify our models robustness, we didnt want to stop at news. We also tested it on SciTLDR-AIC. This dataset consists of scientific abstracts and represents a much harder challenge due to its technical language and high compression ratio. For this task, we aimed to generate a concise 1-sentence summary.​

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