Papers by Tingchao Fu

2 papers
What’s Left Unsaid? Detecting and Correcting Misleading Omissions in Multimodal News Previews (2026.acl-long)

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Challenge: Existing efforts to detect factually incorrect content are omitted by creators who subtly reshape impressions by omitting crucial background context.
Approach: They propose a multi-stage pipeline that simulates preview-based and context-based understanding and a OMGuard pipeline that combines interpretation-aware fine-tuning and rationale-guided misleading content correction.
Outcome: The proposed framework lifts an 8B model’s detection accuracy to the level of a 235B LVLM while delivering stronger end-to-end correction.
Correct When Paired, Wrong When Split: Decoupling and Editing Modality-Specific Neurons in MLLMs (2026.acl-long)

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Challenge: Existing knowledge editing paradigms suffer from editing decoupling failures . entity knowledge is sequestered into disentangled modality-specific pathways .
Approach: They propose a method that explicitly disentangles and localizes modality-specific neuron groups for targeted knowledge.
Outcome: The proposed method outperforms baselines in reliability and consistency while preserving model locality.

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