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Models/RNN

RNN

Reported on 24 benchmarks across 11 tasks · 6 papers · 14 SOTA

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

Time Series13 results

Trajectory PredictiononVi-Fi Multi-modal Dataset
MSE-D· 2024-04-02
15.92
best: 13.42 (OOSTraj)
SOTA
OOSTraj: Out-of-Sight Trajectory Prediction With Vision-Positioning Denoising arXiv:2404.02227
Trajectory PredictiononVi-Fi Multi-modal Dataset
MSE-P· 2024-04-02
15.69
best: 13.83 (OOSTraj)
SOTA
OOSTraj: Out-of-Sight Trajectory Prediction With Vision-Positioning Denoising arXiv:2404.02227
Time Series ForecastingonMLO-Cn2
RMSE· 2024-01-07
0.581
best: 0.428 (GBRT)
SOTA
Effective Benchmarks for Optical Turbulence Modeling arXiv:2401.03573
Time Series ForecastingonUSNA-Cn2 (short-duration)
RMSE· 2024-01-07
0.187
best: 0.16 (GBRT)
SOTA
Effective Benchmarks for Optical Turbulence Modeling arXiv:2401.03573
Time Series AnalysisonMLO-Cn2
RMSE· 2024-01-07
0.581
best: 0.212 (GBRT)
SOTA
Effective Benchmarks for Optical Turbulence Modeling arXiv:2401.03573
Time Series AnalysisonUSNA-Cn2 (short-duration)
RMSE· 2024-01-07
0.187
best: 0.16 (GBRT)
SOTA
Effective Benchmarks for Optical Turbulence Modeling arXiv:2401.03573
Time Series AnalysisonUSNA-Cn2 (long-term)
RMSE· 2024-01-07
0.53
best: 0.458 (Hybrid Air-Water Temperature Difference)
SOTA
Effective Benchmarks for Optical Turbulence Modeling arXiv:2401.03573
Time Series AnalysisonUSNA-Cn2 (short-duration)
RMSE· 2024-01-07
0.375
best: 0.16 (GBRT)
SOTA
Effective Benchmarks for Optical Turbulence Modeling arXiv:2401.03573
Time Series AnalysisonMLO-Cn2
RMSE· 2024-01-07
0.336
best: 0.212 (GBRT)
SOTA
Effective Benchmarks for Optical Turbulence Modeling arXiv:2401.03573
Time Series RegressiononUSNA-Cn2 (long-term)
RMSE· 2024-01-07
0.53
best: 0.458 (Hybrid Air-Water Temperature Difference)
SOTA
Effective Benchmarks for Optical Turbulence Modeling arXiv:2401.03573
Time Series RegressiononUSNA-Cn2 (short-duration)
RMSE· 2024-01-07
0.375
best: 0.178 (Offshore Macro Meteorological)
SOTA
Effective Benchmarks for Optical Turbulence Modeling arXiv:2401.03573
Time Series RegressiononMLO-Cn2
RMSE· 2024-01-07
0.336
best: 0.212 (GBRT)
SOTA
Effective Benchmarks for Optical Turbulence Modeling arXiv:2401.03573
Trajectory PredictiononVi-Fi Multi-modal Dataset
SUM· 2024-04-02
31.61
best: 200.9 (ViTag)
OOSTraj: Out-of-Sight Trajectory Prediction With Vision-Positioning Denoising arXiv:2404.02227

Speech7 results

DialogueonSecond dialogue state tracking challenge
Area
92
DialogueonSecond dialogue state tracking challenge
Food
86
DialogueonSecond dialogue state tracking challenge
Joint
69
best: 85 (Seq2Seq-DU-w/oSchema)
DialogueonSecond dialogue state tracking challenge
Price
86
best: 94 (Neural belief tracker)
DialogueonSecond dialogue state tracking challenge
Request
95.7
best: 97.5 (Zhong et al.)
DialogueonWizard-of-Oz
Joint
70.8
best: 91.37 (AG-DST)
DialogueonWizard-of-Oz
Request
87.1
best: 97.6 (BERT-based tracker)

Graphs2 results

Graph GenerationonToulouse Road Network
StreetMover· 2019-10-31
0.0289
SOTA
Image-Conditioned Graph Generation for Road Network Extraction arXiv:1910.14388
Graph GenerationonToulouse Road Network
StreetMover· 2019-10-31
0.0289
Image-Conditioned Graph Generation for Road Network Extraction arXiv:1910.14388

Natural Language Processing2 results

Czech Text DiacritizationonMultilingual Dataset for Training and Evaluating Diacritics Restoration Systems
Alpha-Word accuracy
98.71
best: 99.22 (BERT)
Vietnamese Text DiacritizationonMultilingual Dataset for Training and Evaluating Diacritics Restoration Systems
Alpha-Word accuracy
97.55
best: 98.53 (BERT)

Music1 result

Music ModelingonNottingham
NLL· 2018-03-04
4.05
SOTA
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling arXiv:1803.01271

Computer Code1 result

Code SearchonCoDesc
Test MRR· 2021-05-29
0.766
best: 0.839 (Self-attention)
CoDesc: A Large Code-Description Parallel Dataset arXiv:2105.14220

Audio1 result

Speech RecognitiononTIMIT
Percentage error· 2018-11-19
16.5
best: 8.3 (wav2vec 2.0)
The PyTorch-Kaldi Speech Recognition Toolkit arXiv:1811.07453