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المنصة
الرئيسية
SOTA
تحليل AMR
Amr Parsing On Ldc2017T10
Amr Parsing On Ldc2017T10
المقاييس
Smatch
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
Smatch
Paper Title
StructBART + MBSE (IBM)
86.7
Maximum Bayes Smatch Ensemble Distillation for AMR Parsing
Graphene Smatch (IBM)
86.26
Ensembling Graph Predictions for AMR Parsing
LeakDistill
86.1
Incorporating Graph Information in Transformer-based AMR Parsing
StructBART + MBSE (IBM)
85.9
Maximum Bayes Smatch Ensemble Distillation for AMR Parsing
Graphene Support (IBM)
85.85
Ensembling Graph Predictions for AMR Parsing
AMRBART large
85.4
Graph Pre-training for AMR Parsing and Generation
ATP-SRL (Ensemble)
85.3
ATP: AMRize Then Parse! Enhancing AMR Parsing with PseudoAMRs
ATP-SRL
85.2
ATP: AMRize Then Parse! Enhancing AMR Parsing with PseudoAMRs
LeakDistill (base)
84.7
Incorporating Graph Information in Transformer-based AMR Parsing
StructBART-J (IBM)
84.7
Structure-aware Fine-tuning of Sequence-to-sequence Transformers for Transition-based AMR Parsing
BiBL+Silver
84.7
BiBL: AMR Parsing and Generation with Bidirectional Bayesian Learning
BiBL
84.6
BiBL: AMR Parsing and Generation with Bidirectional Bayesian Learning
SPRING
84.3
One SPRING to Rule Them Both: Symmetric AMR Semantic Parsing and Generation without a Complex Pipeline
APT base (IBM)
82.6
AMR Parsing with Action-Pointer Transformer
Xu, et al.
81.4
Improving AMR Parsing with Sequence-to-Sequence Pre-training
stack-Transformer + self-learning (IBM)
81.3
Pushing the Limits of AMR Parsing with Self-Learning
Cai and Lam
80.2
AMR Parsing via Graph-Sequence Iterative Inference
ND+AD+LV
80
Levi Graph AMR Parser using Heterogeneous Attention
stack-Transformer (IBM)
79.0
Transition-based Parsing with Stack-Transformers
Zhang et al.
77.0
Broad-Coverage Semantic Parsing as Transduction
0 of 27 row(s) selected.
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