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Coreference Resolution On Conll 2012

Metrics

Avg F1

Results

Performance results of various models on this benchmark

Paper TitleRepository
Maverick_mes83.6Maverick: Efficient and Accurate Coreference Resolution Defying Recent Trends
seq2seq83.3Coreference Resolution through a seq2seq Transition-Based System
CorefQA + SpanBERT-large83.1CorefQA: Coreference Resolution as Query-based Span Prediction-
ASP+T0-3B82.3Autoregressive Structured Prediction with Language Models
wl-coref + RoBERTa81.0Word-Level Coreference Resolution
s2e + Longformer-Large80.3Coreference Resolution without Span Representations
c2f + SpanBERT-Large80.2Coreference Resolution without Span Representations
SpanBERT + Cluster Merging80.2Revealing the Myth of Higher-Order Inference in Coreference Resolution
CorefQA + SpanBERT-base79.9CorefQA: Coreference Resolution as Query-based Span Prediction-
U-MEM* + SpanBERT-large79.6Learning to Ignore: Long Document Coreference with Bounded Memory Neural Networks
c2f-coref + BERT-large76.9BERT for Coreference Resolution: Baselines and Analysis
EE + BERT-large76.61Coreference Resolution with Entity Equalization-
dali-full-anaphora76.4A Cluster Ranking Model for Full Anaphora Resolution
reinforced model + ELMO73.8End-to-end Deep Reinforcement Learning Based Coreference Resolution-
c2f-coref + ELMo73.0Higher-order Coreference Resolution with Coarse-to-fine Inference
e2e-coref + ELMo70.4End-to-end Neural Coreference Resolution
e2e-coref (ensemble)68.8End-to-end Neural Coreference Resolution
e2e-coref (single)67.2End-to-end Neural Coreference Resolution
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Coreference Resolution On Conll 2012 | SOTA | HyperAI