Papers by Mingxi Zou

2 papers
From Implicit Exploration to Structured Reasoning: Guideline and Refinement for LLMs (2025.findings-emnlp)

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Challenge: Existing models rely on implicit exploration, which leads to unstable reasoning paths and lack of error correction.
Approach: They propose a framework that shifts from implicit exploration to structured reasoning through guideline and refinement.
Outcome: The proposed model outperforms strong baselines on the Big-Bench Hard benchmark.
FinHEAR: Human Expertise and Adaptive Risk-Aware Temporal Reasoning for Financial Decision-Making (2025.findings-emnlp)

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Challenge: Large language models often overlook key behavioral patterns underlying human financial behavior.
Approach: FinHEAR is a multi-agent framework for human expertise and Adaptive Risk-aware reasoning.
Outcome: FinHEAR outperforms baseline models in trend forecasting and decision-making.

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