Papers with adaptive focal loss

2 papers
Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge Distillation (2022.findings-acl)

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Challenge: Document-level relation extraction (DocRE) is a more challenging task than sentence-level one.
Approach: They propose a semi-supervised framework for document-level relation extraction with three components . they use an axial attention module for learning the interdependency among entity-pairs .
Outcome: The proposed model outperforms baseline models on two DocRE datasets and outperformed previous models on human annotated data and distantly supervised data.
ERGO: Event Relational Graph Transformer for Document-level Event Causality Identification (2022.coling-1)

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Challenge: Existing methods to identify event-event causal relations in a document are noisy and require heuristic rules or external tools.
Approach: They propose a document-level event-event causality identification framework that uses heuristic rules to design edges between events.
Outcome: The proposed framework outperforms existing state-of-the-art methods on two benchmark datasets.

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