Papers by Saizhuo Wang

2 papers
Alpha-GPT: Human-AI Interactive Alpha Mining for Quantitative Investment (2025.emnlp-demos)

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Challenge: Traditional methods of alpha mining have inherent limitations, especially in implementing the ideas of quant researchers.
Approach: They propose a new alpha mining paradigm by introducing human-AI interaction and a prompt engineering algorithmic framework to implement this paradigm by using large language models.
Outcome: The proposed framework is based on human-AI interaction and large language models and is comparable to human participants in the WorldQuant International Quant Championship.
Golden Touchstone: A Comprehensive Bilingual Benchmark for Evaluating Financial Large Language Models (2025.findings-emnlp)

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Challenge: Existing financial benchmarks suffer from limited language and task coverage, low-quality datasets, and inadequate adaptability for LLM evaluation.
Approach: They propose a bilingual benchmark for financial LLMs that assesses models’ language understanding and generation capabilities.
Outcome: The proposed bilingual benchmark assesses models’ language understanding and generation capabilities.

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