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SotA/Natural Language Processing/Question Answering/TrecQA

Question Answering on TrecQA

Metric: MAP (higher is better)

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#Model↕MAP▼Extra DataPaperDate↕Code
1TANDA DeBERTa-V3-Large + ALL0.954YesStructural Self-Supervised Objectives for Transf...2023-09-15Code
2TANDA-RoBERTa (ASNQ, TREC-QA)0.943YesTANDA: Transfer and Adapt Pre-Trained Transforme...2019-11-11Code
3DeBERTa-V3-Large + SSP0.923NoPre-training Transformer Models with Sentence-Le...2022-05-20-
4Contextual DeBERTa-V3-Large + SSP0.919YesContext-Aware Transformer Pre-Training for Answe...2023-05-24-
5RLAS-BIABC0.913NoRLAS-BIABC: A Reinforcement Learning-Based Answe...2023-01-07-
6RLAS-BIABC0.913NoRLAS-BIABC: A Reinforcement Learning-Based Answe...2023-01-07-
7RoBERTa-Base Joint + MSPP0.911NoParagraph-based Transformer Pre-training for Mul...2022-05-02Code
8RoBERTa-Base + PSD0.903NoPre-training Transformer Models with Sentence-Le...2022-05-20-
9Comp-Clip + LM + LC0.868NoA Compare-Aggregate Model with Latent Clustering...2019-05-30-
10NLP-Capsule0.7773NoTowards Scalable and Reliable Capsule Networks f...2019-06-06Code
11HyperQA0.77NoHyperbolic Representation Learning for Fast and ...2017-07-25Code
12PWIN0.7588No---
13aNMM0.75NoaNMM: Ranking Short Answer Texts with Attention-...2018-01-05Code
14CNN0.711NoDeep Learning for Answer Sentence Selection2014-12-04Code