Papers by Yake Niu

2 papers
Two Challenges, One Solution: Robust Multimodal Learning through Dynamic Modality Recognition and Enhancement (2025.findings-emnlp)

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Challenge: Existing methods require full-modality data during training phase or require explicit annotations to detect missing modalities.
Approach: They propose a Dynamic modality Recognition and Enhancement for Adaptive Multimodal fusion framework that directs selective reconstruction of missing or underperforming modalities.
Outcome: The proposed framework outperforms several baseline and state-of-the-art models on three benchmark datasets.
Better Late Than Never: Model-Agnostic Hallucination Post-Processing Framework Towards Clinical Text Summarization (2024.findings-acl)

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Challenge: Existing methods for generating concise and coherent summaries may include unintended text with hallucinations, causing computational costs.
Approach: They propose a model-agnostic framework to post-process medical hallucinations . MEDAL integrates with any medical summarization model, requiring no additional computational overhead .
Outcome: MEDAL can post-process medical hallucinations without additional computational overhead.

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