S-EEGNet: Electroencephalogram Signal Classification Based on a Separable Convolution Neural Network With Bilinear Interpolation. - Wenkai Huang 001; Yihao Xue; Lingkai Hu; Hantang Liuli (IEEE Access, 2020)

Toward Understanding the Influence of Individual Clients in Federated Learning. - Yihao Xue; Chaoyue Niu; Zhenzhe Zheng; Shaojie Tang 001; Chengfei Lv; Fan Wu 006; Guihai Chen (CoRR, 2020)

Toward Understanding the Influence of Individual Clients in Federated Learning. - Yihao Xue; Chaoyue Niu; Zhenzhe Zheng; Shaojie Tang 001; Chengfei Lyu; Fan Wu 006; Guihai Chen (AAAI, 2021)

Successive Over Relaxation Recurrent Confidence Inference Network Based on Linear Extrapolation. - Wenkai Huang 001; Yihao Xue; Zefeng Xu; Lingkai Hu (IEEE Access, 2021)

Investigating Why Contrastive Learning Benefits Robustness against Label Noise. - Yihao Xue; Kyle Whitecross; Baharan Mirzasoleiman (ICML, 2022)

Superior generalization of smaller models in the presence of significant label noise. - Yihao Xue; Kyle Whitecross; Baharan Mirzasoleiman (CoRR, 2022)

Polyphonic music generation generative adversarial network with Markov decision process. - Wenkai Huang 001; Yihao Xue; Zefeng Xu; Guanglong Peng; Yu Wu (Multim. Tools Appl., 2022)

Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression. - Yihao Xue; Siddharth Joshi 004; Eric Gan; Pin-Yu Chen; Baharan Mirzasoleiman (ICML, 2023)

Eliminating Spurious Correlations from Pre-trained Models via Data Mixing. - Yihao Xue; Ali Payani; Yu Yang 007; Baharan Mirzasoleiman (CoRR, 2023)

Towards Mitigating Spurious Correlations in the Wild: A Benchmark & a more Realistic Dataset. - Siddharth Joshi 004; Yu Yang 007; Yihao Xue; Wenhan Yang; Baharan Mirzasoleiman (CoRR, 2023)

Deep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016. - Xiaohan Chen; Rui Yang 007; Yihao Xue; Mengjie Huang; Roberto Ferrero; Zidong Wang 001 (IEEE Trans. Instrum. Meas., 2023)

A Novel Local Binary Temporal Convolutional Neural Network for Bearing Fault Diagnosis. - Yihao Xue; Rui Yang 007; Xiaohan Chen; Zhongbei Tian; Zidong Wang 001 (IEEE Trans. Instrum. Meas., 2023)

A novel momentum prototypical neural network to cross-domain fault diagnosis for rotating machinery subject to cold-start. - Xiaohan Chen; Rui Yang 007; Yihao Xue; Chao Yang; Baoye Song; Maiying Zhong (Neurocomputing, 2023)

Investigating the Benefits of Projection Head for Representation Learning. - Yihao Xue; Eric Gan; Jiayi Ni; Siddharth Joshi 004; Baharan Mirzasoleiman (ICLR, 2024)

Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift. - Yihao Xue; Siddharth Joshi 004; Dang Nguyen; Baharan Mirzasoleiman (ICLR, 2024)

Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings. - Yihao Xue; Ali Payani; Yu Yang 007; Baharan Mirzasoleiman (ICML, 2024)

Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise. - Yihao Xue; Kyle Whitecross; Baharan Mirzasoleiman (UAI, 2024)

A Review on Transferability Estimation in Deep Transfer Learning. - Yihao Xue; Rui Yang 007; Xiaohan Chen; Weibo Liu 001; Zidong Wang 001; Xiaohui Liu 001 (IEEE Trans. Artif. Intell., 2024)

Separable Convolutional Network-Based Fault Diagnosis for High-Speed Train: A Gossip Strategy-Based Optimization Approach. - Yihao Xue; Rui Yang 007; Xiaohan Chen; Baoye Song; Zidong Wang 001 (IEEE Trans. Ind. Informatics, 2025)

Representations Shape Weak-to-Strong Generalization: Theoretical Insights and Empirical Predictions. - Yihao Xue; Jiping Li; Baharan Mirzasoleiman (CoRR, 2025)

Verify when Uncertain: Beyond Self-Consistency in Black Box Hallucination Detection. - Yihao Xue; Kristjan H. Greenewald; Youssef Mroueh; Baharan Mirzasoleiman (CoRR, 2025)

LoRA is All You Need for Safety Alignment of Reasoning LLMs. - Yihao Xue; Baharan Mirzasoleiman (CoRR, 2025)