4 papers
From the Inside Out: Progressive Distribution Refinement for Confidence Calibration
Xizhong Yang, Yinan Xia, Huiming Wang +1
Leveraging the model's internal information as the self-reward signal in Reinforcement Learning (RL) has received extensive attention due to its label-free nature. While prior work…
Believe Your Model: Distribution-Guided Confidence Calibration
Xizhong Yang, Haotian Zhang, Huiming Wang +1
Large Reasoning Models have demonstrated remarkable performance with the advancement of test-time scaling techniques, which enhances prediction accuracy by generating multiple cand…
Semantic Bridging Domains: Pseudo-Source as Test-Time Connector
Xizhong Yang, Huiming Wang, Ning Xu +1
Distribution shifts between training and testing data are a critical bottleneck limiting the practical utility of models, especially in real-world test-time scenarios. To adapt mod…
Similarity and Dissimilarity Guided Co-association Matrix Construction for Ensemble Clustering
Xu Zhang, Yuheng Jia, Mofei Song +1
Ensemble clustering aggregates multiple weak clusterings to achieve a more accurate and robust consensus result. The Co-Association matrix (CA matrix) based method is the mainstrea…