Metric: Weighted Accuracy (higher is better)
| # | Model↕ | Weighted Accuracy▼ | Extra Data | Paper | Date↕ | Code |
|---|---|---|---|---|---|---|
| 1 | Sepúlveda-Torres R., Vicente M., Saquete E., Lloret E., Palomar M. (2021) | 90.73 | No | - | - | Code |
| 2 | ZAINAB A. JAWAD, AHMED J. OBAID (CNN and DNN with SCM, 2022) | 84.6 | No | Combination Of Convolution Neural Networks And D... | 2022-10-15 | - |
| 3 | Bhatt et al. | 83.08 | No | On the Benefit of Combining Neural, Statistical ... | 2017-12-11 | Code |
| 4 | Bi-LSTM (max-pooling, attention) | 82.23 | No | Combining Similarity Features and Deep Represent... | 2018-11-02 | Code |
| 5 | 3rd place at FNC-1 - Team UCL Machine Reading (Riedel et al., 2017) | 81.72 | No | A simple but tough-to-beat baseline for the Fake... | 2017-07-11 | Code |
| 6 | Neural method from Mohtarami et al. + TF-IDF (Mohtarami et al., 2018) | 81.23 | No | Automatic Stance Detection Using End-to-End Memo... | 2018-04-20 | - |
| 7 | Neural method from Mohtarami et al. (Mohtarami et al., 2018) | 78.97 | No | Automatic Stance Detection Using End-to-End Memo... | 2018-04-20 | - |
| 8 | Baseline based on skip-thought embeddings (Bhatt et al., 2017) | 76.18 | No | On the Benefit of Combining Neural, Statistical ... | 2017-12-11 | Code |
| 9 | Baseline based on word2vec + hand-crafted features (Bhatt et al., 2017) | 72.78 | No | On the Benefit of Combining Neural, Statistical ... | 2017-12-11 | Code |
| 10 | Neural baseline based on bi-directional LSTMs (Bhatt et al., 2017) | 63.11 | Yes | On the Benefit of Combining Neural, Statistical ... | 2017-12-11 | Code |