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Research map / Label-efficient and robust learning / Recognition and long-tail

FRAGE: Frequency-Agnostic Word Representation

NeurIPS 2018 · Label-efficient and robust learning › Recognition and long-tail · approach: Multilingual language representation pretraining · 110 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add adversarial frequency discriminator on embeddings (FRAGE)Skip-gram · RWSpearman: 52.67 -> 58.12Helped
add adversarial frequency discriminator on embeddings (FRAGE)Skip-gram · RG65Spearman: 75.63 -> 78.78Helped
add adversarial frequency discriminator on embeddings (FRAGE)AWD-LSTM · PTB testperplexity: 57.3 -> 56.1Helped
add adversarial frequency discriminator on embeddings (FRAGE)AWD-LSTM-MoS · PTB testperplexity: 54.44 -> 53.31Helped
add adversarial frequency discriminator on embeddings (FRAGE)AWD-LSTM · WT2 testperplexity: 65.8 -> 63.4Helped
add adversarial frequency discriminator on embeddings (FRAGE)AWD-LSTM-MoS + dynamic evaluation · WT2 testperplexity: 40.68 -> 39.14Helped
add adversarial frequency discriminator on embeddings (FRAGE)Transformer Base · WMT14 En-DeBLEU: 27.30 -> 28.36Helped
add adversarial frequency discriminator on embeddings (FRAGE)Transformer Big · WMT14 En-DeBLEU: 28.40 -> 29.11Helped
add adversarial frequency discriminator on embeddings (FRAGE)Transformer · IWSLT14 De-EnBLEU: 33.12 -> 33.97Helped
add adversarial frequency discriminator on embeddings (FRAGE)RCNN · AG's Newsaccuracy: 90.47% -> 91.73%Helped
add adversarial frequency discriminator on embeddings (FRAGE)RCNN · IMDBaccuracy: 92.41% -> 93.07%Helped
add adversarial frequency discriminator on embeddings (FRAGE)RCNN · 20 Newsgroupsaccuracy: 96.49% -> 96.93%Helped

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