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.

Top 10

榜单概览

数据说明

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。

Ranking

模型排名

暂无评测数据。