SSRAN

Reported on 4 benchmarks across 2 tasks · 1 paper · 1 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing4 results

Intent DetectiononMixSNIPS
Accuracy· 2022-11-22
98.4
SOTA
A Scope Sensitive and Result Attentive Model for Multi-Intent Spoken Language Understanding arXiv:2211.12220
Slot FillingonMixSNIPS
Micro F1· 2022-11-22
95.8
best: 97.2 (BiSLU)
A Scope Sensitive and Result Attentive Model for Multi-Intent Spoken Language Understanding arXiv:2211.12220
Slot FillingonMixATIS
Micro F1· 2022-11-22
89.4
best: 90.5 (MISCA)
A Scope Sensitive and Result Attentive Model for Multi-Intent Spoken Language Understanding arXiv:2211.12220
Intent DetectiononMixATIS
Accuracy· 2022-11-22
77.9
best: 83.3 (DGIF)
A Scope Sensitive and Result Attentive Model for Multi-Intent Spoken Language Understanding arXiv:2211.12220