Papers by Yuran Sun

2 papers
From Perceptions to Decisions: Wildfire Evacuation Decision Prediction with Behavioral Theory-informed LLMs (2025.acl-long)

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Challenge: Existing statistical methods for evacuation decision prediction fail to capture complex and diverse behavioral logic of different individuals.
Approach: They propose a Large Language Model (LLM)-based framework that integrates behavioral theories and models to streamline the Chain-of-Thought reasoning and integrates with memory-based Reinforcement Learning module to provide accurate evacuation decision prediction and understanding.
Outcome: The proposed framework improves on three post-wildfire survey datasets with strong cross-event generalizability over existing models.
From Scores to Preferences: Redefining Evaluation Paradigm for Speech Quality Reward Modeling (2026.findings-acl)

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Challenge: Experimental results show that the MOS-aware GRM significantly improves fine-grained speech quality discrimination.
Approach: They propose a MOS-aware reward model that incorporates MOS gap into reward function during reinforcement learning.
Outcome: The proposed model significantly improves fine-grained speech quality discrimination.

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