1 citations · 1 across the 2 of their papers we have counts for
3 papers
Too Good to Be Real? Diagnosing and Reducing the Gap Between AI Preference and Real User Engagement
Xinglang Zhang, Yuanmeng Xiang, Yunyao Zhang +3
Large language models are increasingly used to generate and evaluate online content, yet it remains unclear whether the qualities they associate with higher engagement match what r…
Semiotic logical hexagon theory for LLM logical reasoning
Yunyao Zhang, Xinglang Zhang, Zeliang Chen +2
Large language models (LLMs) have become powerful tools for language understanding and logical reasoning. However, they still make mistakes when a problem requires both understandi…
Logical Phase Transitions: Understanding Collapse in LLM Logical Reasoning
Xinglang Zhang, Yunyao Zhang, ZeLiang Chen +3
Symbolic logical reasoning is a critical yet underexplored capability of large language models (LLMs), providing reliable and verifiable decision-making in high-stakes domains such…