Papers by Mingqian Liu

4 papers
Synthetic Socratic Debates: Examining Persona Effects on Moral Decision and Persuasion Dynamics (2025.emnlp-main)

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Challenge: a study of multi-dimensional persona effects in AI-AI debates shows that personas influence moral stances and debate outcomes . political ideology and personality traits exert the strongest influence, according to our study .
Approach: They propose to use a 6-dimensional persona space to simulate structured debates . they find political ideology and personality traits exert the strongest influence .
Outcome: The study shows that personas affect moral stances and debate outcomes . political ideology and personality traits exert the strongest influence .
Can CLIP Count Stars? An Empirical Study on Quantity Bias in CLIP (2024.findings-emnlp)

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Challenge: Despite its versatility, CLIP-based applications often suffer from misunderstandings regarding user intent, leading to discrepancies between the required number of objects and the actual outputs.
Approach: They empirically evaluate CLIP’s understanding of quantity from text, image, and cross-modal perspectives by carefully designing different experimental settings and datasets.
Outcome: The proposed model has shown significant success in various downstream tasks, including editing, generation, and quality evaluation.
Beyond Benchmarks: A Capability-Based Maturity Model for Systematic AI Integration in Hospitals (2026.findings-acl)

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Challenge: Current Large Language Models (LLMs) excel in standardized tests focused on medical knowledge recall, but not in real-world healthcare scenarios.
Approach: They propose a "capability-based hospital AI Maturity Model" framework that categorizes capabilities into distinct maturity levels . medical artificial intelligence is currently at a critical transition stage from technical verification to deep clinical integration .
Outcome: The proposed model provides a clear, stepwise evolutionary path for hospitals from foundational infrastructure construction to ubiquitous intelligence.
RedOne: Revealing Domain-specific LLM Post-Training in Social Networking Services (2025.emnlp-industry)

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Challenge: Social networking services (SNS) have experienced rapid growth, which has proposed significant challenges for platform content management and interaction quality improvement.
Approach: They propose a domain-specific LLM to break the performance bottleneck of single-task baselines and establish a comprehensive foundation for social networking services.
Outcome: The proposed model achieves an average improvement of 14.02% across 8 major tasks and 7.56% in bilingual evaluation benchmark, compared with baseline models.

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