Papers by Zhicheng Du

2 papers
SRAP-Agent: Simulating and Optimizing Scarce Resource Allocation Policy with LLM-based Agent (2024.findings-emnlp)

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Challenge: Existing research on the allocation of public scarce resources has limitations due to data scarcity and data scariness.
Approach: They propose a framework that integrates Large Language Models into economic simulations . they conduct extensive policy simulation experiments to verify the framework's effectiveness .
Outcome: The proposed framework bridges the gap between theoretical models and real-world dynamics by integrating large language models into economic simulations.
VC4VG: Optimizing Video Captions for Text-to-Video Generation (2025.emnlp-main)

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Challenge: Recent advances in text-to-video generation highlight the critical role of high-quality video-text pairs in training models capable of producing coherent and instruction-aligned videos.
Approach: They propose a caption optimization framework tailored to the needs of T2V models.
Outcome: The proposed framework improves video caption quality and video generation performance.

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