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Coreference Resolution On Ontonotes

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このベンチマークにおける各モデルのパフォーマンス結果

Paper Title
Maverick_mes83.6Maverick: Efficient and Accurate Coreference Resolution Defying Recent Trends
seq2seq83.3Coreference Resolution through a seq2seq Transition-Based System
ASP+T0-3B82.3Autoregressive Structured Prediction with Language Models
caw-coref + RoBERTa81.6CAW-coref: Conjunction-Aware Word-level Coreference Resolution
LingMess81.4LingMess: Linguistically Informed Multi Expert Scorers for Coreference Resolution
wl-coref + RoBERTa81Word-Level Coreference Resolution
U-MEM + Longformer80.9Efficient and Interpretable Neural Models for Entity Tracking
longdoc S (OntoNotes + 60k pseudo-singletons)80.6On Generalization in Coreference Resolution
G2GT SpanBERT-large reduced80.5Graph Refinement for Coreference Resolution
G2GT SpanBERT-large overlap80.2Graph Refinement for Coreference Resolution
longdoc S (ON + PreCo + LitBank + 30k pseudo-singletons)79.6On Generalization in Coreference Resolution
U-MEM* + SpanBERT79.6Learning to Ignore: Long Document Coreference with Bounded Memory Neural Networks
SpanBERT79.6SpanBERT: Improving Pre-training by Representing and Predicting Spans
longdoc S (OntoNotes + PreCo + LitBank)79.2On Generalization in Coreference Resolution
BERT-large76.9BERT for Coreference Resolution: Baselines and Analysis
BERT + EE76.61Coreference Resolution with Entity Equalization
BERT-base73.9BERT for Coreference Resolution: Baselines and Analysis
Reinforced + ELMo73.8End-to-end Deep Reinforcement Learning Based Coreference Resolution
c2f-coref73.0Higher-order Coreference Resolution with Coarse-to-fine Inference
e2e-coref + ELMo + hyperparameter tuning72.3Higher-order Coreference Resolution with Coarse-to-fine Inference
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Coreference Resolution On Ontonotes | SOTA | HyperAI超神経