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Leveraging these extracted aspects, we generate extractive and abstractive summaries of scientific papers. Additionally, we provide a benchmarking corpus containing 1000 aspect-related sentences extracted from 40 scientific articles, which can serve as a valuable resource for evaluating various aspect extraction methods. Experimental findings reveal that our automated aspect extraction system successfully identifies between 86 and 92% of sentences related to each aspect with precision ranging from 84 to 94%. The aspect-based extractive summaries outperformed the original paper abstracts in terms of the Rouge scores as well as in Relevance, Consistency, Fluency, and Coherence dimensions. 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