| #GCDH at WNUT-2020 Task 2: BERT-Based Models for the Detection of Informativeness in English COVID-19 Related Tweets | Nov 1, 2020 | InformativenessTask 2 | —Unverified | 0 |
| SunBear at WNUT-2020 Task 2: Improving BERT-Based Noisy Text Classification with Knowledge of the Data domain | Nov 1, 2020 | Language ModelingLanguage Modelling | —Unverified | 0 |
| Emory at WNUT-2020 Task 2: Combining Pretrained Deep Learning Models and Feature Enrichment for Informative Tweet Identification | Nov 1, 2020 | Task 2 | —Unverified | 0 |
| NHK_STRL at WNUT-2020 Task 2: GATs with Syntactic Dependencies as Edges and CTC-based Loss for Text Classification | Nov 1, 2020 | Graph AttentionSentence | —Unverified | 0 |
| NICT Kyoto Submission for the WMT’20 Quality Estimation Task: Intermediate Training for Domain and Task Adaptation | Nov 1, 2020 | Domain AdaptationLanguage Modeling | —Unverified | 0 |
| ISWARA at WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets using BERT and FastText Embeddings | Nov 1, 2020 | Task 2Word Embeddings | —Unverified | 0 |
| CXP949 at WNUT-2020 Task 2: Extracting Informative COVID-19 Tweets -- RoBERTa Ensembles and The Continued Relevance of Handcrafted Features | Oct 15, 2020 | ClassificationGeneral Classification | CodeCode Available | 0 |
| InfoMiner at WNUT-2020 Task 2: Transformer-based Covid-19 Informative Tweet Extraction | Oct 11, 2020 | Task 2 | CodeCode Available | 0 |
| The NU Voice Conversion System for the Voice Conversion Challenge 2020: On the Effectiveness of Sequence-to-sequence Models and Autoregressive Neural Vocoders | Oct 9, 2020 | Task 2Voice Conversion | —Unverified | 0 |
| NutCracker at WNUT-2020 Task 2: Robustly Identifying Informative COVID-19 Tweets using Ensembling and Adversarial Training | Oct 9, 2020 | Task 2Text Classification | CodeCode Available | 0 |
