Jiaheng Wei

According to our database, Jiaheng Wei authored at least 23 papers between 2020 and 2024.

Collaborative distances:

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

2024

LLM Unlearning via Loss Adjustment with Only Forget Data.

Yaxuan Wang, Jiaheng Wei, Chris Yuhao Liu, Jinlong Pang, Quan Liu, Ankit Parag Shah, Yujia Bao, Yang Liu, Wei Wei

CoRR, 2024

Improving Data Efficiency via Curating LLM-Driven Rating Systems.

Jinlong Pang, Jiaheng Wei, Ankit Parag Shah, Zhaowei Zhu, Yaxuan Wang, Chen Qian, Yang Liu, Yujia Bao, Wei Wei

CoRR, 2024

Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond.

Minghao Liu, Zonglin Di, Jiaheng Wei, Zhongruo Wang, Hengxiang Zhang, Ruixuan Xiao, Haoyu Wang, Jinlong Pang, Hao Chen, Ankit Shah, Hongxin Wei, Xinlei He, Zhaowei Zhao, Haobo Wang, Lei Feng, Jindong Wang, James Davis, Yang Liu

CoRR, 2024

Harnessing Business and Media Insights with Large Language Models.

Yujia Bao, Ankit Parag Shah, Neeru Narang, Jonathan Rivers, Rajeev Maksey, Lan Guan, Louise N. Barrere, Shelley Evenson, Rahul Basole, Connie Miao, Ankit Mehta, Fabien Boulay, Su Min Park, Natalie E. Pearson, Eldhose Joy, Tiger He, Sumiran Thakur, Koustav Ghosal, Josh On, Phoebe Morrison, Tim Major, Eva Siqi Wang, Gina Escobar, Jiaheng Wei, Tharindu Cyril Weerasooriya, Queena Song, Daria Lashkevich, Clare Chen, Gyuhak Kim, Dengpan Yin, Don Hejna, Mo Nomeli, Wei Wei

CoRR, 2024

Memorization in deep learning: A survey.

Jiaheng Wei, Yanjun Zhang, Leo Yu Zhang, Ming Ding, Chao Chen, Kok-Leong Ong, Jun Zhang, Yang Xiang

CoRR, 2024

Measuring and Reducing LLM Hallucination without Gold-Standard Answers via Expertise-Weighting.

Jiaheng Wei, Yuanshun Yao, Jean-Francois Ton, Hongyi Guo, Andrew Estornell, Yang Liu

CoRR, 2024

Human-Instruction-Free LLM Self-Alignment with Limited Samples.

Hongyi Guo, Yuanshun Yao, Wei Shen, Jiaheng Wei, Xiaoying Zhang, Zhaoran Wang, Yang Liu

CoRR, 2024

2023

Client-side Gradient Inversion Against Federated Learning from Poisoning.

Jiaheng Wei, Yanjun Zhang, Leo Yu Zhang, Chao Chen, Shirui Pan, Kok-Leong Ong, Jun Zhang, Yang Xiang

CoRR, 2023

Do humans and machines have the same eyes? Human-machine perceptual differences on image classification.

Minghao Liu, Jiaheng Wei, Yang Liu, James Davis

CoRR, 2023

Fairness Improves Learning from Noisily Labeled Long-Tailed Data.

Jiaheng Wei, Zhaowei Zhu, Gang Niu, Tongliang Liu, Sijia Liu, Masashi Sugiyama, Yang Liu

CoRR, 2023

Distributionally Robust Post-hoc Classifiers under Prior Shifts.

Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Auditing for Federated Learning: A Model Elicitation Approach.

Yang Liu, Rixing Lou, Jiaheng Wei

Proceedings of the Fifth International Conference on Distributed Artificial Intelligence, 2023

To Aggregate or Not? Learning with Separate Noisy Labels.

Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu

Proceedings of the 4th Crowd Science Workshop on Collaboration of Humans and Learning Algorithms for Data Labeling co-located with ACM International WSDM Conference (WSDM 2023), 2023

2022

Consensus on Dynamic Stochastic Block Models: Fast Convergence and Phase Transitions.

Haoyu Wang, Jiaheng Wei, Zhenyuan Zhang

CoRR, 2022

To Smooth or Not? When Label Smoothing Meets Noisy Labels.

Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Masashi Sugiyama, Yang Liu

Proceedings of the International Conference on Machine Learning, 2022

Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations.

Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu, Yang Liu

Proceedings of the Tenth International Conference on Learning Representations, 2022

DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training.

Jiaheng Wei, Minghao Liu, Jiahao Luo, Andrew Zhu, James Davis, Yang Liu

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Induced Domain Adaptation.

Yang Liu, Yatong Chen, Jiaheng Wei

CoRR, 2021

Understanding (Generalized) Label Smoothing when Learning with Noisy Labels.

Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Yang Liu

CoRR, 2021

PeerGAN: Generative Adversarial Networks with a Competing Peer Discriminator.

Jiaheng Wei, Minghao Liu, Jiahao Luo, Qiutong Li, James Davis, Yang Liu

CoRR, 2021

When Optimizing f-Divergence is Robust with Label Noise.

Jiaheng Wei, Yang Liu

Proceedings of the 9th International Conference on Learning Representations, 2021

Sample Elicitation.

Jiaheng Wei, Zuyue Fu, Yang Liu, Xingyu Li, Zhuoran Yang, Zhaoran Wang

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Incentives for Federated Learning: a Hypothesis Elicitation Approach.

Yang Liu, Jiaheng Wei

CoRR, 2020