Papers by Boqi Chen

4 papers
Mask What Matters: Mitigating Object Hallucinations in Multimodal Large Language Models with Object-Aligned Visual Contrastive Decoding (2026.eacl-srw)

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Challenge: Recent studies improve visual contrastive decoding (VCD) by constructing more informative auxiliary views.
Approach: They propose to construct an object-aligned auxiliary view that disrupts unsupported tokens and produces a stronger contrast signal.
Outcome: Empirically, the proposed method shows consistent gains on two popular object hallucination benchmarks across two MLLMs.
Seeing Beyond: Enhancing Visual Question Answering with Multi-Modal Retrieval (2025.coling-industry)

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Challenge: Multi-modal Large language models still suffer from model hallucination and lack of specific knowledge when answering challenging questions.
Approach: They propose to use a multi-modal retrieval augmented generation method to integrate knowledge from all modalities into a model to enable alignment between query and knowledge.
Outcome: The proposed method achieves significant performance improvement on the VQA dataset.
MEDSYN: Benchmarking Multi-EviDence SYNthesis in Complex Clinical Cases for Multimodal Large Language Models (2026.findings-acl)

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Challenge: Existing benchmarks for multimodal large language models do not capture real-world clinical complexity.
Approach: They evaluate multilingual, multimodal multimodal models of clinical cases with up to 7 distinct visual clinical evidence types per case.
Outcome: The proposed model outperforms human models on differential diagnosis (DDx) generation and final diagnosis (FDx) selection.
Detecting Frames in News Headlines and Lead Images in U.S. Gun Violence Coverage (2021.findings-emnlp)

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Challenge: Journalists have been using both text and images to frame news stories . lead images may carry additional background knowledge about the event .
Approach: They find that combining lead images and contextual information with text improves news framing . they release the first multimodal news framming dataset related to gun violence in the u.s.
Outcome: The study shows that combining lead images with text improves prediction of news frames . it also shows that using multiple modes of information improves frame image relevance .

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