Papers by Haiqin Zhong

2 papers
Beyond Prompt Engineering: A Systematic Analysis of Prompt Lexical Sensitivity and Its Impacts on Quality (2026.findings-acl)

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Challenge: Existing studies on prompt engineering have focused on optimizing models for performance under stylistic perturbations.
Approach: They conduct the first analysis of n-gram token-level mechanisms . they find that higher average performance is inherently associated with lower variance and greater stability.
Outcome: The proposed model reduces the variance of the generated code by 40% . the proposed model is based on a large-scale dataset of 132,000 prompt variants .
EAGLE: Expert-Guided Self-Enhancement for Preference Alignment in Pathology Large Vision-Language Model (2025.acl-long)

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Challenge: Recent advances in Large Vision Language Models (LVLMs) show promise for pathological diagnosis, yet their application in clinical settings faces critical challenges of multimodal hallucination and biased responses.
Approach: They propose a framework that integrates medical expertise into preference alignment.
Outcome: The proposed framework outperforms existing pathological LVLMs while maintaining pathological accuracy.

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