Papers with RRL

3 papers
Coupling Local Context and Global Semantic Prototypes via a Hierarchical Architecture for Rhetorical Roles Labeling (2026.eacl-long)

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Challenge: Hierarchical models capture local dependencies but lack global, corpus-level representations.
Approach: They propose two prototype-based methods that integrate local context with global representations to address this limitation.
Outcome: The proposed methods integrate local context with global representations.
HiCuLR: Hierarchical Curriculum Learning for Rhetorical Role Labeling of Legal Documents (2024.findings-emnlp)

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Challenge: Existing approaches overlook the varying difficulty levels inherent in legal document discourse styles and rhetorical roles.
Approach: They propose a hierarchical curriculum learning framework for RRL that nests two curricula: Rhetorical Role-level Curriculum (RC) on the outer layer and Document-level curriculum (DC) on inner layer.
Outcome: The proposed framework is based on four legal document datasets and shows that it is complementary to existing models.
Mind Your Neighbours: Leveraging Analogous Instances for Rhetorical Role Labeling for Legal Documents (2024.lrec-main)

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Challenge: Rhetorical Role Labeling (RRL) of legal judgments presents challenges such as inferring sentence roles from context, interrelated roles, limited annotated data, and label imbalance.
Approach: They propose techniques to enhance RRL performance by leveraging knowledge from semantically similar instances.
Outcome: The proposed methods achieve remarkable improvements in challenging macro-F1 scores.

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