Papers with zero-shot knowledge transfer

2 papers
DLIR: Spherical Adaptation for Cross-Lingual Knowledge Transfer of Sociological Concepts Alignment (2025.findings-emnlp)

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Challenge: Existing methods for identifying nuanced sociological concepts fail to capture domain-specific subtleties or require extensive parallel data.
Approach: a new approach to aligning nuanced sociological concepts is proposed . a dual-branch LoRA approach captures core semantics and counteracts specific language perturbations.
Outcome: a new approach outperforms baselines on cross-lingual sociological concept retrieval across 10 languages.
Generalizing over Long Tail Concepts for Medical Term Normalization (2022.emnlp-main)

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Challenge: Medical term normalization is a task of mapping a text to a large number of output classes.
Approach: They propose a learning strategy that leverages hierarchical information to enhance generalizability of models.
Outcome: The proposed strategy produces state-of-the-art performance on seen concepts and consistent improvements on unseen ones, allowing efficient zero-shot knowledge transfer across text typologies and datasets.

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