Math Word Problem Solving on Math23K (test)
87.1AccuracyMulti-view
Evaluation Results
| Method | Links | |
|---|---|---|
| Multi-viewCategory=Consistent Multi-View Learning, Pre-trained language model=true2022.10 | 87.1 | |
| Ana-CLModel Category=Seq2Seq/Tree2023.10 | 85.6 | |
| M-ViewModel Category=Seq2Exp2023.10 | 85.6 | |
| Gen&RankPre-training architecture=Seq2Seq pre-train2021.07 | 85.4 | |
| Gen-RankCategory=Seq2Seq, Pre-trained language model=true2022.10 | 85.4 | |
| RE-DeductionCategory=I-RE, Pre-trained language model=true2022.10 | 85.4 | |
| RankModel Category=Seq2Seq/Tree, reproduced=true2023.10 | 85.4 | |
| RE-ExtModel Category=Seq2Exp2023.10 | 85.4 | |
| Generate & Ranktraining=multi-task training2021.09 | 85.4 | |
| Textual-CLModel Category=Seq2Seq/Tree2023.10 | 85 | |
| ElasticModel Category=Seq2Exp, reproduced=true2023.10 | 84.8 | |
| MWP-BERTPre-training architecture=Encoder pre-train, Pre-training=MWP pre-training and fine-tuning2021.07 | 84.7 | |
| MWP-RoBERTaPre-training architecture=Encoder pre-train, Pre-training=MWP pre-training and fine-tuning2021.07 | 84.5 | |
| BERT-TreeCategory=Structure-Gen, Pre-trained language model=true2022.10 | 84.4 | |
| BERT-TModel Category=Seq2Seq/Tree2023.10 | 84.4 | |
| MWP-NASModel Category=Seq2Exp2023.10 | 84.4 | |
| RPKHS2021.07 | 83.9 | |
| H-ReasonerCategory=Structure-Gen, Pre-trained language model=true2022.10 | 83.9 | |
| H-ReasonerModel Category=Seq2Seq/Tree2023.10 | 83.9 | |
| BERTPre-training architecture=Encoder pre-train, Pre-training=None2021.07 | 83.8 | |
| RoBERTaPre-training architecture=Encoder pre-train, Pre-training=None2021.07 | 83.5 | |
| Logic-DecModel Category=Seq2Seq/Tree2023.10 | 83.4 | |
| BERT-CLPre-training architecture=Seq2Seq pre-train2021.07 | 83.2 | |
| CL-PrototypeCategory=CL-Gen, Pre-trained language model=true2022.10 | 83.2 | |
| PrototypeModel Category=Seq2Seq/Tree2023.10 | 83.2 | |
| M-TreeModel Category=Seq2Exp2023.10 | 82.5 | |
| REAL2021.09 | 82.3 | |
| REALPre-training architecture=Seq2Seq pre-train2021.07 | 82.3 | |
| mBARTtraining=fine-tuning2021.09 | 80.8 | |
| T-DisCategory=CL-Gen, Pre-trained language model=true2022.10 | 79.1 | |
| T-DisModel Category=Seq2Seq/Tree2023.10 | 79.1 | |
| E-PointerModel Category=Seq2Exp, reproduced=true2023.10 | 78.7 | |
| EEH-G2T2021.07 | 78.5 | |
| Multi-E/D2021.09 | 78.4 | |
| NumS2T2021.07 | 78.1 | |
| DAGCategory=I-RE, Pre-trained language model=true2022.10 | 77.5 | |
| DAGModel Category=Seq2Exp2023.10 | 77.5 | |
| TSN-MD2021.09 | 77.4 | |
| Graph2Tree2021.09 | 77.4 | |
| Graph2Tree2021.07 | 77.4 | |
| TSN-MD2021.07 | 77.4 | |
| Graph2TreeCategory=Structure-Gen, Pre-trained language model=false2022.10 | 77.4 | |
| G2TModel Category=Seq2Seq/Tree2023.10 | 77.4 | |
| Graph2Tree2021.09 | 77.4 | |
| RoGenCategory=Seq2Seq, Pre-trained language model=true2022.10 | 76.9 | |
| PLM-GenModel Category=Seq2Seq/Tree2023.10 | 76.9 | |
| BERTGenCategory=Seq2Seq, Pre-trained language model=true2022.10 | 76.6 | |
| BERTGenModel Category=Seq2Seq/Tree2023.10 | 76.6 | |
| KA-S2T2021.07 | 76.3 | |
| NS-Solver2021.07 | 75.7 | |
| NS-Solver2021.07 | 75.67 | |
| GTS2021.09 | 75.6 | |
| GTS2021.07 | 75.6 | |
| GTSCategory=Structure-Gen, Pre-trained language model=false2022.10 | 75.6 | |
| GTSModel Category=Seq2Seq/Tree2023.10 | 75.6 | |
| GTS2021.09 | 75.6 | |
| TSN-MD2021.07 | 75.1 | |
| mBERTCategory=Seq2Seq, Pre-trained language model=true2022.10 | 75.1 | |
| mBERTModel Category=Seq2Seq/Tree2023.10 | 75.1 | |
| GTS2021.07 | 74.3 | |
| GroupAttnCategory=Seq2Seq, Pre-trained language model=false2022.10 | 69.5 | |
| GroupAttnModel Category=Seq2Seq/Tree2023.10 | 69.5 | |
| Group-ATT2021.09 | 69.5 | |
| AST-Dec2021.09 | 69 | |
| T-RNN2021.09 | 66.9 | |
| T-RNN2021.09 | 66.9 | |
| Math-EN2021.09 | 66.7 | |
| Math-EN2021.07 | 66.7 | |
| Math-EN2021.09 | 66.7 | |
| Self-ConsistencyModel Category=LLM, reproduced=true2023.10 | 66.1 | |
| StackDecoder2021.07 | 66 | |
| DNS2021.07 | 58.1 | |
| gpt-3.5-turboModel Category=LLM, reproduced=true2023.10 | 54.8 |