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Constituency Grammar Induction On Ptb

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Max F1 (WSJ)

Résultats

Résultats de performance de divers modèles sur ce benchmark

Paper Title
PRPN38.1Neural Language Modeling by Jointly Learning Syntax and Lexicon
Ensemble (Selective MBR)-Ensemble Distillation for Unsupervised Constituency Parsing
ReCAT-Augmenting Transformers with Recursively Composed Multi-grained Representations
ON-LSTM49.4Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
DIORA (+PP)56.2Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Auto-Encoders
Parse-Focused (NT=30)68.4Structural Optimization Ambiguity and Simplicity Bias in Unsupervised Neural Grammar Induction
Ensemble (Generative MBR)71.9Ensemble Distillation for Unsupervised Constituency Parsing
inside-outside co-training + weak supervision66.8Co-training an Unsupervised Constituency Parser with Weak Supervision
Compound PCFG60.1Compound Probabilistic Context-Free Grammars for Grammar Induction
TN-PCFG (p=500)61.4PCFGs Can Do Better: Inducing Probabilistic Context-Free Grammars with Many Symbols
ON-LSTM (tuned)50.0Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
DIORA49.6Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Auto-Encoders
URNNG52.4Unsupervised Recurrent Neural Network Grammars
GPST(left to right parsing)-Generative Pretrained Structured Transformers: Unsupervised Syntactic Language Models at Scale
Neural PCFG52.6Compound Probabilistic Context-Free Grammars for Grammar Induction
Parse-Focused (NT=4500)70.3Structural Optimization Ambiguity and Simplicity Bias in Unsupervised Neural Grammar Induction
S-DIORA63.96Unsupervised Parsing with S-DIORA: Single Tree Encoding for Deep Inside-Outside Recursive Autoencoders
DP in rank space-Dynamic Programming in Rank Space: Scaling Structured Inference with Low-Rank HMMs and PCFGs
Hashing (Parserker 2)64.1On Eliciting Syntax from Language Models via Hashing
PRPN (tuned)47.9Neural Language Modeling by Jointly Learning Syntax and Lexicon
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