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Combining Deep Generative Models and Multi-lingual Pretraining for Semi-supervised Document Classification ...
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It Is Not As Good As You Think! Evaluating Simultaneous Machine Translation on Interpretation Data ...
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A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
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Self-Alignment Pretraining for Biomedical Entity Representations
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Liu, Fangyu; Shareghi, Ehsan; Meng, Zaiqiao. - : Association for Computational Linguistics, 2021. : Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021
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A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
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Abstract:
Few-shot crosslingual transfer has been shown to outperform its zero-shot counterpart with pretrained encoders like multilingual BERT. Despite its growing popularity, little to no attention has been paid to standardizing and analyzing the design of few-shot experiments. In this work, we highlight a fundamental risk posed by this shortcoming, illustrating that the model exhibits a high degree of sensitivity to the selection of few shots. We conduct a large-scale experimental study on 40 sets of sampled few shots for six diverse NLP tasks across up to 40 languages. We provide an analysis of success and failure cases of few-shot transfer, which highlights the role of lexical features. Additionally, we show that a straightforward full model finetuning approach is quite effective for few-shot transfer, outperforming several state-of-the-art few-shot approaches. As a step towards standardizing few-shot crosslingual experimental designs, we make our sampled few shots publicly available. ... : ACL-IJCNLP 2021 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2012.15682 https://dx.doi.org/10.48550/arxiv.2012.15682
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Show Some Love to Your n-grams: A Bit of Progress and Stronger n-gram Language Modeling Baselines ...
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Fast, Small and Exact: Infinite-order Language Modelling with Compressed Suffix Trees ...
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Structured Prediction of Sequences and Trees using Infinite Contexts ...
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