Papers by Dongnan Yang

2 papers
RWKV-CLIP: A Robust Vision-Language Representation Learner (2024.emnlp-main)

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Challenge: Using large image-text datasets, large-scale image-data sets have been used for visionlanguage pre-training.
Approach: They propose a framework that leverages Large Language Models to combine and refine information from web-based image-text pairs, synthetic captions, and detection tags.
Outcome: The proposed framework can combine and refine information from web-based image-text pairs, synthetic captions, and detection tags.
Dual-Path Dynamic Fusion with Learnable Query for Multimodal Sentiment Analysis (2025.emnlp-main)

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Challenge: Existing methods for multimodal sentiment analysis struggle with global and fine-grained contributions and over-reliance on text.
Approach: They propose a multimodal sentiment analysis architecture that processes inputs through two complementary paths: global and local.
Outcome: The proposed architecture achieves state-of-the-art in fine-grained sentiment prediction on the CMU-MOSI and CMU MOSEI benchmarks.

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