Papers with non-hyperbolic loss functions

1 papers
Jump To Hyperspace: Comparing Euclidean and Hyperbolic Loss Functions for Hierarchical Multi-Label Text Classification (2025.coling-main)

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Challenge: Hierarchical Multi-Label Text Classification (HMTC) is a challenging machine learning task . a recent study evaluated the effectiveness of Euclidean and hyperbolic loss functions on HMTC .
Approach: They evaluate label-aware and contrastive losses in the Euclidean and hyperbolic space . they find contrastive loss functions are less effective when deployed in the hyperbolical space compared to non-hyperbolic ones .
Outcome: The proposed model improves on four commonly used HMTC datasets.

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