Papers by Hanqian Wu

3 papers
Cross-media User Profiling with Joint Textual and Social User Embedding (C18-1)

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Challenge: Empirical studies demonstrate the effectiveness of the proposed approach to cross-media user profiling tasks.
Approach: They propose a uniform user embedding learning approach to address cross-media user profiling by bridging the knowledge between the source and target media.
Outcome: Empirical results show that the proposed approach performs well on two cross-media user profiling tasks.
DiVE: Decoupling Intra-layer Visual Evidence for Mitigating Hallucinations in Large Vision-Language Models (2026.acl-long)

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Challenge: Existing decoding-based approaches do not explicitly decouple visual evidence from mixed vision–language representations.
Approach: They propose to decouple visual evidence from mixed vision–language representations by dynamically identifying layers enriched with visual information and performing intra-layer decoupling to extract aggregated visual evidence.
Outcome: Experiments show that DiVE achieves state-of-the-art performance on multiple benchmarks.
More than Text: Multi-modal Chinese Word Segmentation (2021.acl-short)

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Challenge: Currently, word segmentation is performed in many languages without word delimiters.
Approach: They propose to combine the multi-modality to perform Chinese word segmentation . they propose a time-dependent multi-module interactive model to integrate multi-modality information .
Outcome: The proposed model integrates multi-modal information for word sequence labeling with Chinese language as target . the proposed model performs well on three training sets on Chinese and other languages without word delimiters.

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