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Dependency Parsing On Penn Treebank

المقاييس

LAS
POS
UAS

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج
LAS
POS
UAS
Paper TitleRepository
Andor et al.92.7997.4494.61Globally Normalized Transition-Based Neural Networks-
CRFPar94.49-96.14Efficient Second-Order TreeCRF for Neural Dependency Parsing-
Deep Biaffine + RoBERTa95.75-97.29Deep Biaffine Attention for Neural Dependency Parsing-
MFVI95.34-96.91Second-Order Neural Dependency Parsing with Message Passing and End-to-End Training-
SpanRel94.70-96.44Generalizing Natural Language Analysis through Span-relation Representations-
Distilled neural FOG92.0697.4494.26Distilling an Ensemble of Greedy Dependency Parsers into One MST Parser-
Deep Biaffine94.22-95.87Deep Biaffine Attention for Neural Dependency Parsing-
Graph-based parser with GNNs94.3197.395.97Graph-based Dependency Parsing with Graph Neural Networks-
Label Attention Layer + HPSG + XLNet96.2697.397.42Rethinking Self-Attention: Towards Interpretability in Neural Parsing-
jPTDP93.8797.9795.51An improved neural network model for joint POS tagging and dependency parsing-
Weiss et al.92.0697.394.01Structured Training for Neural Network Transition-Based Parsing-
RNG Transformer95.01-96.66Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement-
HPSG Parser (Joint) + XLNet 95.7297.397.20Head-Driven Phrase Structure Grammar Parsing on Penn Treebank-
CVT + Multi-Task95.02-96.61Semi-Supervised Sequence Modeling with Cross-View Training-
DMPar + XLNet95.92-97.30Enhancing Structure-aware Encoder with Extremely Limited Data for Graph-based Dependency Parsing
Left-to-Right Pointer Network94.43-96.04Left-to-Right Dependency Parsing with Pointer Networks-
BIST transition-based parser91.997.4493.99Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations-
Arc-hybrid91.4297.393.56Training with Exploration Improves a Greedy Stack-LSTM Parser-
Stack-Pointer Network94.1997.395.87Stack-Pointer Networks for Dependency Parsing-
BIST graph-based parser91.097.393.1Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations-
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Dependency Parsing On Penn Treebank | SOTA | HyperAI