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Integrating Vectorized Lexical Constraints for Neural Machine Translation ...
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Contextual Semantic-Guided Entity-Centric GCN for Relation Extraction
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In: Mathematics; Volume 10; Issue 8; Pages: 1344 (2022)
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Virtual Reality-Integrated Immersion-Based Teaching to English Language Learning Outcome
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In: Front Psychol (2022)
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Alternated Training with Synthetic and Authentic Data for Neural Machine Translation ...
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CPM-2: Large-scale Cost-effective Pre-trained Language Models ...
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VISITRON: Visual Semantics-Aligned Interactively Trained Object-Navigator ...
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Assessing Multilingual Fairness in Pre-trained Multimodal Representations ...
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Dialog{S}um: {A} Real-Life Scenario Dialogue Summarization Dataset ...
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Transfer Learning for Sequence Generation: from Single-source to Multi-source ...
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Segment, Mask, and Predict: Augmenting Chinese Word Segmentation with Self-Supervision ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.158/ Abstract: Recent state-of-the-art (SOTA) effective neural network methods and fine-tuning methods based on pre-trained models (PTM) have been used in Chinese word segmentation (CWS), and they achieve great results. However, previous works focus on training the models with the fixed corpus at every iteration. The intermediate generated information is also valuable. Besides, the robustness of the previous neural methods is limited by the large-scale annotated data. There are a few noises in the annotated corpus. Limited efforts have been made by previous studies to deal with such problems. In this work, we propose a self-supervised CWS approach with a straightforward and effective architecture. First, we train a word segmentation model and use it to generate the segmentation results. Then, we use a revised masked language model (MLM) to evaluate the quality of the segmentation results based on the predictions of the MLM. Finally, we leverage ...
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Keyword:
Computational Linguistics; Language Models; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Neural Network
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URL: https://underline.io/lecture/37641-segment,-mask,-and-predict-augmenting-chinese-word-segmentation-with-self-supervision https://dx.doi.org/10.48448/axyx-nt90
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Learning to Selectively Learn for Weakly-supervised Paraphrase Generation ...
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SWSR: A Chinese Dataset and Lexicon for Online Sexism Detection ...
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Analyzing the Limits of Self-Supervision in Handling Bias in Language ...
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Statistically significant detection of semantic shifts using contextual word embeddings ...
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SWSR: A Chinese Dataset and Lexicon for Online Sexism Detection ...
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Statistically Significant Detection of Semantic Shifts using Contextual Word Embeddings ...
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Leveraging Word-Formation Knowledge for Chinese Word Sense Disambiguation ...
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SWSR: A Chinese Dataset and Lexicon for Online Sexism Detection ...
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