Papers by Siyue Li

2 papers
Rethinking Composed Image Retrieval Evaluation: A Fine-Grained Benchmark from Image Editing (2026.acl-long)

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Challenge: Composed Image Retrieval (CIR) is a complex task in multimodal understanding . current CIR benchmarks lack a robust evaluation pipeline and limited query categories .
Approach: They construct a fine-grained CIR benchmark that allows for precise control over modification types and content.
Outcome: The proposed benchmark covers 5,000 high-quality queries structured across five main categories and fifteen subcategories.
VQAGuider: Guiding Multimodal Large Language Models to Answer Complex Video Questions (2025.acl-long)

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Challenge: Multimodal large language models (MLLMs) can grasp the intention of a question and decomposing it to a series of visual recognition sub-tasks to find out the answer with the help of an agent.
Approach: They propose a framework for multimodal large language models to grasp the intention of a question and decompose it into a series of visual recognition sub-tasks to find out the answer.
Outcome: The proposed framework improves the accuracy of complex video-related questions by 29.6% and 17.2% on CVQA and the existing VQA datasets.

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