Papers by Shengqian Qin

3 papers
MMXU: A Multi-Modal and Multi-X-ray Understanding Dataset for Disease Progression (2025.findings-acl)

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Challenge: Existing datasets and models fail to consider critical aspects of medical diagnostics, authors argue . MMXU enables multi-image questions incorporating both current and historical patient data.
Approach: They propose a dataset for MedVQA that focuses on identifying changes in specific regions between two patient visits.
Outcome: The proposed dataset improves diagnostic accuracy by 20% by integrating historical data.
Meta-Tool: Unleash Open-World Function Calling Capabilities of General-Purpose Large Language Models (2025.acl-long)

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Challenge: Large language models struggle with addressing diverse user inquiries in open-world tasks.
Approach: They propose a plug-and-play tool retrieval system for LLMs to access external tool library and use retrieved tools to solve user's problem.
Outcome: The proposed model improves on a finetuned version of LLaMA-3.1 and 2,800 dialogues and 7,361 tools spanning ten distinct test categories.
MedMCP-Calc: Benchmarking LLMs for Realistic Medical Calculator Scenarios via MCP Integration (2026.acl-long)

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Challenge: Existing benchmarks focus on static single-step calculations with explicit instructions.
Approach: They propose a benchmark for evaluating medical calculators in realistic scenarios . they use 118 scenario tasks across 4 clinical domains to evaluate medical calculator performance .
Outcome: The first benchmark for evaluating medical calculators in realistic scenarios is released . it features 118 scenario tasks across 4 clinical domains and is based on a model context protocol integration.

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