HyperAI超神经

Long Range Modeling On Scrolls

评估指标

Avg.
CNLI
GovRep
Nrtv
QALT EM-T/H
QMSum
Qspr
SumScr

评测结果

各个模型在此基准测试上的表现结果

比较表格
模型名称Avg.CNLIGovRepNrtvQALT EM-T/HQMSumQsprSumScr
longt5-efficient-text-to-text-transformer-for38.685.657.7 / 30.0 / 31.423.037.9 / 36.633.9 / 11.0 / 22.846.634.8 / 9.6 / 21.1
adapting-pretrained-text-to-text-models-for39.7687.159.4 / 29.8 / 30.826.237.8 / 34.035.1 / 11.0 / 22.048.737.7 / 10.2 / 21.5
efficient-long-text-understanding-with-short37.9987.357.5 / 26.3 / 27.424.134.8 / 34.834.2 / 11.0 / 22.046.935.2 / 8.7 / 19.4
longt5-efficient-text-to-text-transformer-for42.5388.261.1 / 32.3 / 33.729.346.0 / 42.134.9 / 11.8 / 23.553.135.8 / 9.6 / 21.1
longt5-efficient-text-to-text-transformer-for41.0387.361.3/32.2/33.827.240.6 / 38.635.1 / 12.0 / 23.352.360.3 / 31.1 / 32.8
scrolls-standardized-comparison-over-long19.356645.3 / 17.9 / 20.81.525.2 / 26.114.2 / 2.0 / 9.33.419.6 / 1.8 / 11.0
unifying-language-learning-paradigms-88.7------
scrolls-standardized-comparison-over-long29.0177.447.9 / 18.6 / 22.715.426.0 / 25.930.2 / 8.7 / 20.726.327.2 / 4.9 / 16.7
investigating-efficiently-extending--59.3 / 29.3 / 30.9--32.9 / 9.8 / 21.4- 35.0 / 8.9 / 20.4
scrolls-standardized-comparison-over-long--------
colt5-faster-long-range-transformers-with43.5188.461.3/32.2/33.831.148.1/43.836.2/12.9/24.353.936.4/10.2/21.7
unifying-language-learning-paradigms37.87-53.6 / 26.1 / 28.824.245.8 / 40.731.1 / 8.5 / 20.437.632.9 / 7.8 / 19.4
investigating-efficiently-extending--60.3 / 30.0 / 31.5--33.2 / 9.6 / 21.6 -35.7 / 9.1 / 20.6