5 papers · 2 filters
Confidence Comes from Experience: Experiential Confidence Estimation from Reasoning to Agents
Caiqi Zhang, Xiaochen Zhu, Chengzu Li +3
Reliable confidence estimation is increasingly central to the trustworthy deployment of language models: a calibrated estimate of the probability that an output is correct decides…
Code Is More Than Text: Uncertainty Estimation for Code Generation
Yuling Shi, Caiqi Zhang, Yuexian Li +4
Large language models (LLMs) are increasingly deployed as code generators, where silently wrong programs pose real safety and reliability risks. Reliable uncertainty estimation (UE…
When Calibration Rankings Reverse: Accuracy-Controlled Evaluation for Fair Comparison of LLMs
Zhichao Yang, Caiqi Zhang, Ruihan Yang +3
Calibration evaluates whether a model confidence aligns with its empirical accuracy. Existing studies often compare the calibration of different large language models using global…
Demystifying Multi-Agent Debate: The Role of Confidence and Diversity
Xiaochen Zhu, Caiqi Zhang, Yizhou Chi +3
Multi-agent debate (MAD) is widely used to improve large language model (LLM) performance through test-time scaling, yet recent work shows that vanilla MAD often underperforms simp…
Confidence Estimation for LLMs in Multi-turn Interactions
Caiqi Zhang, Ruihan Yang, Xiaochen Zhu +5
While confidence estimation is a promising direction for mitigating hallucinations in Large Language Models (LLMs), current research overwhelmingly focuses on single-turn settings.…