6 papers
LEC: Linear Expectation Constraints for Selection-Conditioned Risk Control in Selective Prediction and Routing Systems
Zhiyuan Wang, Aniri, Tianlong Chen +4
Foundation models often generate unreliable answers, while heuristic uncertainty estimators fail to fully distinguish correct from incorrect outputs, causing users to accept errone…
SConU: Selective Conformal Uncertainty in Large Language Models
Zhiyuan Wang, Qingni Wang, Yue Zhang +4
As large language models are increasingly utilized in real-world applications, guarantees of task-specific metrics are essential for their reliable deployment. Previous studies hav…
Optimizing Robustness and Accuracy in Mixture of Experts: A Dual-Model Approach
Xu Zhang, Kaidi Xu, Ziqing Hu +1
Mixture of Experts (MoE) have shown remarkable success in leveraging specialized expert networks for complex machine learning tasks. However, their susceptibility to adversarial at…
ConU: Conformal Uncertainty in Large Language Models with Correctness Coverage Guarantees
Zhiyuan Wang, Jinhao Duan, Lu Cheng +6
Uncertainty quantification (UQ) in natural language generation (NLG) tasks remains an open challenge, exacerbated by the closed-source nature of the latest large language models (L…
Word-Sequence Entropy: Towards Uncertainty Estimation in Free-Form Medical Question Answering Applications and Beyond
Zhiyuan Wang, Jinhao Duan, Chenxi Yuan +6
Uncertainty estimation is crucial for the reliability of safety-critical human and artificial intelligence (AI) interaction systems, particularly in the domain of healthcare engine…
I'm Spartacus, No, I'm Spartacus: Measuring and Understanding LLM Identity Confusion
Kun Li, Shichao Zhuang, Yue Zhang +5
Large Language Models (LLMs) excel in diverse tasks such as text generation, data analysis, and software development, making them indispensable across domains like education, busin…