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SotA/Natural Language Processing/Natural Language Inference/RTE

Natural Language Inference on RTE

Metric: Accuracy (higher is better)

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#Model↕Accuracy▼Extra DataPaperDate↕Code
1PSQ (Chen et al., 2020)86.8NoA Statistical Framework for Low-bitwidth Trainin...2020-10-27Code
2Q8BERT (Zafrir et al., 2019)84.8NoQ8BERT: Quantized 8Bit BERT2019-10-14Code
3Q-BERT (Shen et al., 2020)84.7NoQ-BERT: Hessian Based Ultra Low Precision Quanti...2019-09-12-
4KiC-770M74NoKnowledge-in-Context: Towards Knowledgeable Semi...2022-10-28-
5Flipped-3B71.05NoGuess the Instruction! Flipped Learning Makes La...2022-10-06Code
6RoE-3B64.01NoExploring the Benefits of Training Expert Langua...2023-02-07Code
7ELC-BERT-base 98M (zero init)63NoNot all layers are equally as important: Every L...2023-11-03-
8ELC-BERT-small 24M55.4NoNot all layers are equally as important: Every L...2023-11-03-
9LTG-BERT-base 98M54.7NoNot all layers are equally as important: Every L...2023-11-03-
10LTG-BERT-small 24M53.7NoNot all layers are equally as important: Every L...2023-11-03-