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1
Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse​ ...
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2
Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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3
Phrase-Level Action Reinforcement Learning for Neural Dialog Response Generation ...
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4
Correcting Chinese Spelling Errors with Phonetic Pre-training ...
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5
PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction ...
Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.233 Abstract: Chinese spelling correction (CSC) is a task to detect and correct spelling errors in texts. CSC is essentially a linguistic problem, thus the ability of language understanding is crucial to this task. In this paper, we propose a Pre-trained masked Language model with Misspelled knowledgE (PLOME) for CSC, which jointly learns how to understand language and correct spelling errors. To this end, PLOME masks the chosen tokens with similar characters according to a confusion set rather than the fixed token ``[MASK]" as in BERT. Besides character prediction, PLOME also introduces pronunciation prediction to learn the misspelled knowledge on phonic level. Moreover, phonological and visual similarity knowledge is important to this task. PLOME utilizes GRU networks to model such knowledge based on characters' phonics and strokes. Experiments are conducted on widely used benchmarks. Our method achieves superior performance against state-of-the-art ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/25563-plome-pre-training-with-misspelled-knowledge-for-chinese-spelling-correction
https://dx.doi.org/10.48448/hvyh-zh15
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6
Including Signed Languages in Natural Language Processing ...
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7
When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation ...
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8
To POS Tag or Not to POS Tag: The Impact of POS Tags on Morphological Learning in Low-Resource Settings ...
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9
Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words ...
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10
HIT - A Hierarchically Fused Deep Attention Network for Robust Code-mixed Language Representation ...
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11
Minimally-Supervised Morphological Segmentation using Adaptor Grammars with Linguistic Priors ...
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12
LearnDA: Learnable Knowledge-Guided Data Augmentation for Event Causality Identification ...
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13
Quotation Recommendation and Interpretation Based on Transformation from Queries to Quotations ...
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14
How Did This Get Funded?! Automatically Identifying Quirky Scientific Achievements ...
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15
Minimax and Neyman–Pearson Meta-Learning for Outlier Languages ...
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16
CLINE: Contrastive Learning with Semantic Negative Examples for Natural Language Understanding ...
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17
Towards Protecting Vital Healthcare Programs by Extracting Actionable Knowledge from Policy ...
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18
DYPLOC: Dynamic Planning of Content Using Mixed Language Models for Text Generation ...
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19
Automated Concatenation of Embeddings for Structured Prediction ...
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20
QASR: QCRI Aljazeera Speech Resource A Large Scale Annotated Arabic Speech Corpus ...
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