Yihao Xue

According to our database, Yihao Xue authored at least 22 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

LoRA is All You Need for Safety Alignment of Reasoning LLMs.

Yihao Xue, Baharan Mirzasoleiman

CoRR, July, 2025

Verify when Uncertain: Beyond Self-Consistency in Black Box Hallucination Detection.

Yihao Xue, Kristjan H. Greenewald, Youssef Mroueh, Baharan Mirzasoleiman

CoRR, February, 2025

Representations Shape Weak-to-Strong Generalization: Theoretical Insights and Empirical Predictions.

Yihao Xue, Jiping Li, Baharan Mirzasoleiman

CoRR, February, 2025

Separable Convolutional Network-Based Fault Diagnosis for High-Speed Train: A Gossip Strategy-Based Optimization Approach.

Yihao Xue, Rui Yang, Xiaohan Chen, Baoye Song, Zidong Wang

IEEE Trans. Ind. Informatics, January, 2025

2024

A Review on Transferability Estimation in Deep Transfer Learning.

Yihao Xue, Rui Yang, Xiaohan Chen, Weibo Liu, Zidong Wang, Xiaohui Liu

IEEE Trans. Artif. Intell., December, 2024

Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise.

Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman

Proceedings of the Uncertainty in Artificial Intelligence, 2024

Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings.

Yihao Xue, Ali Payani, Yu Yang, Baharan Mirzasoleiman

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift.

Yihao Xue, Siddharth Joshi, Dang Nguyen, Baharan Mirzasoleiman

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Investigating the Benefits of Projection Head for Representation Learning.

Yihao Xue, Eric Gan, Jiayi Ni, Siddharth Joshi, Baharan Mirzasoleiman

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

A novel momentum prototypical neural network to cross-domain fault diagnosis for rotating machinery subject to cold-start.

Xiaohan Chen, Rui Yang, Yihao Xue, Chao Yang, Baoye Song, Maiying Zhong

Neurocomputing, October, 2023

A Novel Local Binary Temporal Convolutional Neural Network for Bearing Fault Diagnosis.

Yihao Xue, Rui Yang, Xiaohan Chen, Zhongbei Tian, Zidong Wang

IEEE Trans. Instrum. Meas., 2023

Deep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016.

Xiaohan Chen, Rui Yang, Yihao Xue, Mengjie Huang, Roberto Ferrero, Zidong Wang

IEEE Trans. Instrum. Meas., 2023

Towards Mitigating Spurious Correlations in the Wild: A Benchmark & a more Realistic Dataset.

Siddharth Joshi, Yu Yang, Yihao Xue, Wenhan Yang, Baharan Mirzasoleiman

CoRR, 2023

Eliminating Spurious Correlations from Pre-trained Models via Data Mixing.

Yihao Xue, Ali Payani, Yu Yang, Baharan Mirzasoleiman

CoRR, 2023

Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression.

Yihao Xue, Siddharth Joshi, Eric Gan, Pin-Yu Chen, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2023

2022

Polyphonic music generation generative adversarial network with Markov decision process.

Wenkai Huang, Yihao Xue, Zefeng Xu, Guanglong Peng, Yu Wu

Multim. Tools Appl., 2022

Superior generalization of smaller models in the presence of significant label noise.

Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman

CoRR, 2022

Investigating Why Contrastive Learning Benefits Robustness against Label Noise.

Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2022

2021

Successive Over Relaxation Recurrent Confidence Inference Network Based on Linear Extrapolation.

Wenkai Huang, Yihao Xue, Zefeng Xu, Lingkai Hu

IEEE Access, 2021

Toward Understanding the Influence of Individual Clients in Federated Learning.

Yihao Xue, Chaoyue Niu, Zhenzhe Zheng, Shaojie Tang, Chengfei Lyu, Fan Wu, Guihai Chen

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Toward Understanding the Influence of Individual Clients in Federated Learning.

Yihao Xue, Chaoyue Niu, Zhenzhe Zheng, Shaojie Tang, Chengfei Lv, Fan Wu, Guihai Chen

CoRR, 2020

S-EEGNet: Electroencephalogram Signal Classification Based on a Separable Convolution Neural Network With Bilinear Interpolation.

Wenkai Huang, Yihao Xue, Lingkai Hu, Hantang Liuli

IEEE Access, 2020