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Computer Science > Computation and Language

Title: ReflectSumm: A Benchmark for Course Reflection Summarization

Abstract: This paper introduces ReflectSumm, a novel summarization dataset specifically designed for summarizing students' reflective writing. The goal of ReflectSumm is to facilitate developing and evaluating novel summarization techniques tailored to real-world scenarios with little training data, %practical tasks with potential implications in the opinion summarization domain in general and the educational domain in particular. The dataset encompasses a diverse range of summarization tasks and includes comprehensive metadata, enabling the exploration of various research questions and supporting different applications. To showcase its utility, we conducted extensive evaluations using multiple state-of-the-art baselines. The results provide benchmarks for facilitating further research in this area.
Comments: LREC-COLING 2024 camera ready; code and dataset are available at this https URL
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2403.19012 [cs.CL]
  (or arXiv:2403.19012v2 [cs.CL] for this version)

Submission history

From: Yang Zhong [view email]
[v1] Wed, 27 Mar 2024 21:10:07 GMT (1909kb,D)
[v2] Tue, 23 Apr 2024 02:28:10 GMT (1909kb,D)

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