9 papers
Measuring Judgment Quality in Natural-Language Explanations: Evidence from Forecasting Tournaments
Christopher W. Karvetski, Sheldon S. Huang, Simas KuÄinskas +4
Decision-makers routinely rely on expert judgments accompanied by written explanations, yet explanation quality is difficult to measure at scale. Forecasting tournaments offer a na…
Adaptive Interviewing for Persona Simulation in LLMs: Evidence-Grounded Reasoning Improves Decision Alignment
Ruoxi Su, Yuhan Liu, Jingyu Hu
Accurately simulating the decisions of a specific individual remains challenging for large language models (LLMs), partly because persona information is often provided as static de…
StakeBench: Evaluating Language Understanding Grounded in Market Commitment
Yunhua Pei, Jingyu Hu, Yiwei Shi +3
Existing financial NLP benchmarks often rely on labels supplied by outside observers, measuring how language is perceived rather than what speakers have committed to in the market.…
Influencing LLM Multi-Agent Dialogue via Policy-Parameterized Prompts
Hongbo Bo, Jingyu Hu, Weiru Liu
Large Language Models (LLMs) have emerged as a new paradigm for multi-agent systems. However, existing research on the behaviour of LLM-based multi-agents relies on ad hoc prompts…
MONICA: Real-Time Monitoring and Calibration of Chain-of-Thought Sycophancy in Large Reasoning Models
Jingyu Hu, Shu Yang, Xilin Gong +3
Large Reasoning Models (LRMs) suffer from sycophantic behavior, where models tend to agree with users' incorrect beliefs and follow misinformation rather than maintain independent…
Large Vision-Language Model Alignment and Misalignment: A Survey Through the Lens of Explainability
Dong Shu, Haiyan Zhao, Jingyu Hu +4
Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities in processing both visual and textual information. However, the critical challenge of alignment betwe…