Benchmark
QMSum
summarization
long_context
text
QMSum is a benchmark for query-based multi-domain meeting summarization consisting of 1,808 query-summary pairs over 232 meetings across academic, product, and committee domains. The dataset enables models to select and summarize relevant spans of meetings in response to specific queries. Published at NAACL 2021, QMSum presents significant challenges in long meeting summarization where models must identify and summarize relevant content based on user queries.
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分数为 0-100 百分制综合成绩(Elo 榜为相对评分,仅供同榜内比较)。评测分数属事实数据,整理自公开评测体系与厂商公开资料,部分分数为厂商自报口径,不同榜单的评测方法与数据集可能存在差异,请结合多个榜单交叉参考。
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