5 papers
A Unified Framework for In-Context Learning with Causal and Masked Language Models
Chenrui Liu, Chuanlong Xie, Falong Tan +2
In-context learning (ICL) has emerged as a central capability of pretrained language models, yet its theoretical analysis has focused primarily on causal language models trained by…
Empirical Likelihood-Based Fairness Auditing: Distribution-Free Certification and Flagging
Jie Tang, Chuanlong Xie, Xianli Zeng +1
Machine learning models in high-stakes applications, such as recidivism prediction and automated personnel selection, often exhibit systematic performance disparities across sensit…
Benchmarking Out-of-Distribution Detection for Plankton Recognition: A Systematic Evaluation of Advanced Methods in Marine Ecological Monitoring
Yingzi Han, Jiakai He, Chuanlong Xie +1
Automated plankton recognition models face significant challenges during real-world deployment due to distribution shifts (Out-of-Distribution, OoD) between training and test data.…
In-Context Learning as Nonparametric Conditional Probability Estimation: Risk Bounds and Optimality
Chenrui Liu, Falong Tan, Chuanlong Xie +2
This paper investigates the expected excess risk of in-context learning (ICL) for multiclass classification. We formalize each task as a sequence of labeled examples followed by a…
DSDE: Using Proportion Estimation to Improve Model Selection for Out-of-Distribution Detection
Jingyao Geng, Yuan Zhang, Jiaqi Huang +4
Model library is an effective tool for improving the performance of single-model Out-of-Distribution (OoD) detector, mainly through model selection and detector fusion. However, ex…