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Longformer Coreference Joint
L
Longformer Coreference Joint
Developed by shtoshni
A coreference resolution model fine-tuned based on the Longformer-large architecture, trained on a mixed dataset of OntoNotes, LitBank, and PreCo, designed to address coreference issues in text.
Downloads 22
Release Time : 3/2/2022
Model Overview
This model is specifically designed for coreference resolution tasks, capable of identifying the specific entities referred to by pronouns or noun phrases in text. It requires integration with a document encoder and is part of the paper 'Longformer: The Long-Document Transformer'.
Model Features
Long Text Processing Capability
Based on the Longformer architecture, it supports coreference resolution in long documents
Multi-dataset Training
Fine-tuned on a mixed dataset of three coreference resolution datasets: OntoNotes, LitBank, and PreCo
Attention Mechanism Optimization
Employs a local+global attention mechanism to balance efficiency and performance in long text processing
Model Capabilities
Coreference Resolution
Long Text Processing
Entity Linking Identification
Use Cases
Natural Language Processing
Document Understanding Systems
Used to build more accurate document understanding systems by resolving coreference issues in text
Improves the coherence of entity recognition in document understanding systems
Question Answering Systems
Enhances the ability of QA systems to understand pronoun references in text
Increases the accuracy of pronoun reference resolution in complex texts for QA systems
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