https://github.com/teffland/expected-statistic-regularization
공식 코드Improving Low-Resource Cross-lingual Parsing with Expected Statistic Regularization
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Dependency parsing is the task of extracting a dependency parse of a sentence that represents its grammatical structure and defines the relationships between "head" words and words, which modify those heads.
Example:
root
|
| +-------dobj---------+
| | |
nsubj | | +------det-----+ | +-----nmod------+
+--+ | | | | | | |
| | | | | +-nmod-+| | | +-case-+ |
+ | + | + + || + | + | |
I prefer the morning flight through Denver
Relations among the words are illustrated above the sentence with directed, labeled arcs from heads to dependents (+ indicates the dependent).
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Improving Low-Resource Cross-lingual Parsing with Expected Statistic Regularization
Diversity-Aware Batch Active Learning for Dependency Parsing
On Difficulties of Cross-Lingual Transfer with Order Differences: A Case Study on Dependency Parsing
On the Sensitivity and Stability of Model Interpretations in NLP
ÚFAL LatinPipe at EvaLatin 2024: Morphosyntactic Analysis of Latin
ÚFAL MRPipe at MRP 2019: UDPipe Goes Semantic in the Meaning Representation Parsing Shared Task
ÚFAL at MultiLexNorm 2021: Improving Multilingual Lexical Normalization by Fine-tuning ByT5
VICTR: Visual Information Captured Text Representation for Text-to-Image Multimodal Tasks
Extracting Temporal Event Relation with Syntax-guided Graph Transformer
Universal Dependencies Parsing for Colloquial Singaporean English
Second-Order Neural Dependency Parsing with Message Passing and End-to-End Training
Second-Order Semantic Dependency Parsing with End-to-End Neural Networks
Cross-lingual Dependency Parsing with Unlabeled Auxiliary Languages
Effective Token Graph Modeling using a Novel Labeling Strategy for Structured Sentiment Analysis
On Extended Long Short-term Memory and Dependent Bidirectional Recurrent Neural Network
Efficient Second-Order TreeCRF for Neural Dependency Parsing
Semantic Role Labeling as Dependency Parsing: Exploring Latent Tree Structures Inside Arguments
Fine-Grained Emotion Classification of Chinese Microblogs Based on Graph Convolution Networks
Transition-Based Dependency Parsing with Stack Long Short-Term Memory
Systematic Inequalities in Language Technology Performance across the World's Languages
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.