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Amr Parsing On Ldc2017T10

Metrics

Smatch

Results

Performance results of various models on this benchmark

Paper Title
StructBART + MBSE (IBM)86.7Maximum Bayes Smatch Ensemble Distillation for AMR Parsing
Graphene Smatch (IBM)86.26Ensembling Graph Predictions for AMR Parsing
LeakDistill86.1Incorporating Graph Information in Transformer-based AMR Parsing
StructBART + MBSE (IBM)85.9Maximum Bayes Smatch Ensemble Distillation for AMR Parsing
Graphene Support (IBM)85.85Ensembling Graph Predictions for AMR Parsing
AMRBART large85.4Graph Pre-training for AMR Parsing and Generation
ATP-SRL (Ensemble)85.3ATP: AMRize Then Parse! Enhancing AMR Parsing with PseudoAMRs
ATP-SRL85.2ATP: AMRize Then Parse! Enhancing AMR Parsing with PseudoAMRs
LeakDistill (base)84.7Incorporating Graph Information in Transformer-based AMR Parsing
StructBART-J (IBM)84.7Structure-aware Fine-tuning of Sequence-to-sequence Transformers for Transition-based AMR Parsing
BiBL+Silver84.7BiBL: AMR Parsing and Generation with Bidirectional Bayesian Learning
BiBL84.6BiBL: AMR Parsing and Generation with Bidirectional Bayesian Learning
SPRING84.3One SPRING to Rule Them Both: Symmetric AMR Semantic Parsing and Generation without a Complex Pipeline
APT base (IBM)82.6AMR Parsing with Action-Pointer Transformer
Xu, et al.81.4Improving AMR Parsing with Sequence-to-Sequence Pre-training
stack-Transformer + self-learning (IBM)81.3Pushing the Limits of AMR Parsing with Self-Learning
Cai and Lam80.2AMR Parsing via Graph-Sequence Iterative Inference
ND+AD+LV80Levi Graph AMR Parser using Heterogeneous Attention
stack-Transformer (IBM)79.0Transition-based Parsing with Stack-Transformers
Zhang et al.77.0Broad-Coverage Semantic Parsing as Transduction
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