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Intent Detection on ATIS (test)

1.57Intent ErrorJoint model with recurrent intent + slot label context
1.44882.26693.0853.9031Sep 6, 2016

Evaluation results

MethodLinks
Joint model with recurrent intent + slot label contextintent context=recurrent, slot label context=yes2016.091.57—
Joint model with local & recurrent slot label contextslot label context=local & recurrent2016.091.68—
Joint model with local & recurrent intent + slot label contextintent context=local & recurrent, slot label context=yes2016.091.68—
Joint model with local & recurrent intent contextintent context=local & recurrent2016.091.79—
Joint model with local slot label contextslot label context=local2016.091.79—
Joint model with recurrent slot label contextslot label context=recurrent2016.091.79—
Joint model with local intent contextintent context=local2016.091.9—
Joint model with recurrent intent contextintent context=recurrent2016.091.9—
Joint model with local intent + slot label contextintent context=local, slot label context=yes2016.091.9—
Basic joint training model2016.092.02—
Independent training RNN intent model2016.092.13—
RecNN2016.094.6—
RecNN+Viterbi2016.094.6—
BERTBASEParams (M)=110, Latency (ms)=1580, Speedup=1.0x2021.10—97.16
Capsule-NLU2021.10—95
DistilBERTParams (M)=66, Latency (ms)=781, Speedup=2.0x2021.10—96.98
LIDSNet2021.10—95.97
LIDSNetParams (M)=0.065, Latency (ms)=18, Speedup=87.0x2021.10—95.97
MobileBERTParams (M)=24.6, Latency (ms)=545, Speedup=2.9x2021.10—96.3
SF-ID (BLSTM) network2021.10—97.76
Slot-Gated BiLSTM with Attention2021.10—94.1
Stack-Propagation2021.10—96.9
Stack-Propagation + BERT2021.10—97.5
TinyBERT4Params (M)=14.5, Latency (ms)=162, Speedup=9.8x2021.10—95.97