Papers by Ning Pang

2 papers
Dynamic-prototype Contrastive Fine-tuning for Continual Few-shot Relation Extraction with Unseen Relation Detection (2025.coling-main)

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Challenge: Existing approaches to learn relations from labeled data overlook task interference in continual learning and memory requirements for different relations.
Approach: They propose a framework to learn new relations from limited labeled data while preserving knowledge about previously learned relations.
Outcome: The proposed framework is more practical and comprehensive for real-world scenarios.
DREAM: Improving Video-Text Retrieval Through Relevance-Based Augmentation Using Large Foundation Models (2025.naacl-long)

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Challenge: Recent advances in video-text retrieval models have limited training data annotations.
Approach: They propose a Video-Text Retrieval Paradigm with Relevance-based Augmentation which enhances video and text data using large foundation models to learn more generalized features.
Outcome: The proposed method improves video-text retrieval performance over existing methods.

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