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1
Characterizing News Portrayal of Civil Unrest in Hong Kong, 1998–2020 ...
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2
Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse​ ...
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3
Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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4
Sample-efficient Linguistic Generalizations through Program Synthesis: Experiments with Phonology Problems ...
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5
The Match-Extend Serialization Algorithm in Multiprecedence ...
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6
Recognizing Reduplicated Forms: Finite-State Buffered Machines ...
Abstract: Total reduplication is common in natural language phonology and morphology. However, formally as copying on reduplicants of unbounded size, unrestricted total reduplication requires computational power beyond context-free, while other phonological and morphological patterns are regular, or even sub-regular. Thus, existing language classes characterizing reduplicated strings inevitably include typologically unattested context-free patterns, such as reversals. This paper extends regular languages to incorporate reduplication by introducing a new computational device: finite state buffered machine (FSBMs). We give its mathematical definitions and discuss some closure properties of the corresponding set of languages. As a result, the class of regular languages and languages derived from them through a copying mechanism is characterized. Suggested by previous literature, this class of languages should approach the characterization of natural language word sets. ...
Keyword: Computational Linguistics; Condensed Matter Physics; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://dx.doi.org/10.48448/94rx-t487
https://underline.io/lecture/30083-recognizing-reduplicated-forms-finite-state-buffered-machines
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7
Correcting Chinese Spelling Errors with Phonetic Pre-training ...
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8
PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction ...
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9
Including Signed Languages in Natural Language Processing ...
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10
When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation ...
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11
The Reading Machine: a Versatile Framework for Studying Incremental Parsing Strategies ...
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12
To POS Tag or Not to POS Tag: The Impact of POS Tags on Morphological Learning in Low-Resource Settings ...
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13
Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words ...
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14
LearnDA: Learnable Knowledge-Guided Data Augmentation for Event Causality Identification ...
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15
Quotation Recommendation and Interpretation Based on Transformation from Queries to Quotations ...
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16
How Did This Get Funded?! Automatically Identifying Quirky Scientific Achievements ...
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17
Minimax and Neyman–Pearson Meta-Learning for Outlier Languages ...
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18
CLINE: Contrastive Learning with Semantic Negative Examples for Natural Language Understanding ...
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19
Towards Protecting Vital Healthcare Programs by Extracting Actionable Knowledge from Policy ...
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20
DYPLOC: Dynamic Planning of Content Using Mixed Language Models for Text Generation ...
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