Incentives for Federated Learning: a Hypothesis Elicitation Approach. - Yang Liu 018; Jiaheng Wei (CoRR, 2020)

Sample Elicitation. - Jiaheng Wei; Zuyue Fu; Yang Liu 018; Xingyu Li; Zhuoran Yang; Zhaoran Wang 001 (AISTATS, 2021)

When Optimizing f-Divergence is Robust with Label Noise. - Jiaheng Wei; Yang Liu 018 (ICLR, 2021)

PeerGAN: Generative Adversarial Networks with a Competing Peer Discriminator. - Jiaheng Wei; Minghao Liu 009; Jiahao Luo; Qiutong Li; James Davis 001; Yang Liu 018 (CoRR, 2021)

Understanding (Generalized) Label Smoothing when Learning with Noisy Labels. - Jiaheng Wei; Hangyu Liu; Tongliang Liu; Gang Niu 001; Yang Liu 018 (CoRR, 2021)

Induced Domain Adaptation. - Yang Liu 018; Yatong Chen; Jiaheng Wei (CoRR, 2021)

DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training. - Jiaheng Wei; Minghao Liu 009; Jiahao Luo; Andrew Zhu; James Davis 001; Yang Liu 018 (ECCV (23), 2022)

Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations. - Jiaheng Wei; Zhaowei Zhu; Hao Cheng 005; Tongliang Liu; Gang Niu 001; Yang Liu 018 (ICLR, 2022)

To Smooth or Not? When Label Smoothing Meets Noisy Labels. - Jiaheng Wei; Hangyu Liu; Tongliang Liu; Gang Niu 001; Masashi Sugiyama; Yang Liu 018 (ICML, 2022)

Consensus on Dynamic Stochastic Block Models: Fast Convergence and Phase Transitions. - Haoyu Wang; Jiaheng Wei; Zhenyuan Zhang (CoRR, 2022)

To Aggregate or Not? Learning with Separate Noisy Labels. - Jiaheng Wei; Zhaowei Zhu; Tianyi Luo; Ehsan Amid; Abhishek Kumar; Yang Liu 018 (CSW@WSDM, 2023)

Auditing for Federated Learning: A Model Elicitation Approach. - Yang Liu 018; Rixing Lou; Jiaheng Wei (DAI, 2023)

Distributionally Robust Post-hoc Classifiers under Prior Shifts. - Jiaheng Wei; Harikrishna Narasimhan; Ehsan Amid; Wen-Sheng Chu; Yang Liu 018; Abhishek Kumar (ICLR, 2023)

Fairness Improves Learning from Noisily Labeled Long-Tailed Data. - Jiaheng Wei; Zhaowei Zhu; Gang Niu 001; Tongliang Liu; Sijia Liu 001; Masashi Sugiyama; Yang Liu 018 (CoRR, 2023)

Do humans and machines have the same eyes? Human-machine perceptual differences on image classification. - Minghao Liu 009; Jiaheng Wei; Yang Liu 018; James Davis 001 (CoRR, 2023)

Client-side Gradient Inversion Against Federated Learning from Poisoning. - Jiaheng Wei; Yanjun Zhang; Leo Yu Zhang; Chao Chen 015; Shirui Pan; Kok-Leong Ong; Jun Zhang 010; Yang Xiang 001 (CoRR, 2023)

Human-Instruction-Free LLM Self-Alignment with Limited Samples. - Hongyi Guo; Yuanshun Yao; Wei Shen; Jiaheng Wei; Xiaoying Zhang; Zhaoran Wang 001; Yang Liu 018 (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 018 (CoRR, 2024)

Memorization in deep learning: A survey. - Jiaheng Wei; Yanjun Zhang; Leo Yu Zhang; Ming Ding 001; Chao Chen 015; Kok-Leong Ong; Jun Zhang 010; Yang Xiang 001 (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; et al. (CoRR, 2024)

Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond. - Minghao Liu 009; Zonglin Di; Jiaheng Wei; Zhongruo Wang; Hengxiang Zhang; Ruixuan Xiao; Haoyu Wang 001; Jinlong Pang; Hao Chen 102; Ankit Shah 001; Hongxin Wei; Xinlei He 001; et al. (CoRR, 2024)

Improving Data Efficiency via Curating LLM-Driven Rating Systems. - Jinlong Pang; Jiaheng Wei; Ankit Parag Shah; Zhaowei Zhu; Yaxuan Wang; Chen Qian 001; Yang Liu 018; Yujia Bao; Wei Wei 019 (CoRR, 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 018; Wei Wei 019 (CoRR, 2024)

Reassessing Layer Pruning in LLMs: New Insights and Methods. - Yao Lu; Hao Cheng; Yujie Fang; Zeyu Wang 011; Jiaheng Wei; Dongwei Xu; Qi Xuan 001; Xiaoniu Yang; Zhaowei Zhu (CoRR, 2024)

On the Generalization Ability of Machine-Generated Text Detectors. - Yule Liu; Zhiyuan Zhong; Yifan Liao; Zhen Sun 001; Jingyi Zheng; Jiaheng Wei; Qingyuan Gong; Fenghua Tong; Yang Chen 001; Yang Zhang 016; Xinlei He 001 (CoRR, 2024)

Human and AI Perceptual Differences in Image Classification Errors. - Minghao Liu 009; Jiaheng Wei; Yang Liu 018; James Davis 001 (AAAI, 2025)

Improving Data Efficiency via Curating LLM-Driven Rating Systems. - Jinlong Pang; Jiaheng Wei; Ankit Shah 001; Zhaowei Zhu; Yaxuan Wang; Chen Qian 001; Yang Liu 018; Yujia Bao; Wei Wei 019 (ICLR, 2025)

LLM Unlearning via Loss Adjustment with Only Forget Data. - Yaxuan Wang; Jiaheng Wei; Chris Yuhao Liu; Jinlong Pang; Quan Liu; Ankit Shah 001; Yujia Bao; Yang Liu 018; Wei Wei 019 (ICLR, 2025)

Extracting Private Training Data in Federated Learning From Clients. - Jiaheng Wei; Yanjun Zhang; Leo Yu Zhang; Chao Chen 015; Shirui Pan; Kok-Leong Ong; Jun Zhang 010; Yang Xiang 001 (IEEE Trans. Inf. Forensics Secur., 2025)

Dual-Color Space Hierarchical Classification Network for Image-Sharing Chain Detection. - Jiaheng Wei; Heng Yao; Na Wang; Chuan Qin 001 (IEEE Trans. Instrum. Meas., 2025)

Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning. - Jinlong Pang; Na Di; Zhaowei Zhu; Jiaheng Wei; Hao Cheng; Chen Qian 001; Yang Liu (CoRR, 2025)

GUARD: Generation-time LLM Unlearning via Adaptive Restriction and Detection. - Zhijie Deng; Chris Yuhao Liu; Zirui Pang; Xinlei He 001; Lei Feng 006; Qi Xuan; Zhaowei Zhu; Jiaheng Wei (CoRR, 2025)

FragFake: A Dataset for Fine-Grained Detection of Edited Images with Vision Language Models. - Zhen Sun 001; Ziyi Zhang; Zeren Luo; Zeyang Sha; Tianshuo Cong; Zheng Li; Shiwen Cui; Weiqiang Wang; Jiaheng Wei; Xinlei He 001; Qi Li 002; Qian Wang 002 (CoRR, 2025)

When VLMs Meet Image Classification: Test Sets Renovation via Missing Label Identification. - Zirui Pang; Haosheng Tan; Yuhan Pu; Zhijie Deng; Zhouan Shen; Keyu Hu; Jiaheng Wei (CoRR, 2025)

RULE: Reinforcement UnLEarning Achieves Forget-Retain Pareto Optimality. - Chenlong Zhang; Zhuoran Jin; Hongbang Yuan; Jiaheng Wei; Tong Zhou; Kang Liu 001; Jun Zhao 001; Yubo Chen 001 (CoRR, 2025)

Better Reasoning with Less Data: Enhancing VLMs Through Unified Modality Scoring. - Mingjie Xu; Andrew Estornell; Hongzheng Yang; Yuzhi Zhao; Zhaowei Zhu; Qi Xuan; Jiaheng Wei (CoRR, 2025)

Athena: Enhancing Multimodal Reasoning with Data-efficient Process Reward Models. - Shuai Wang; Zhenhua Liu; Jiaheng Wei; Xuanwu Yin; Dong Li; Emad Barsoum (CoRR, 2025)

Recognition through Reasoning: Reinforcing Image Geo-localization with Large Vision-Language Models. - Ling Li; Yao Zhou; Yuxuan Liang; Fugee Tsung; Jiaheng Wei (CoRR, 2025)

Incentivizing High-quality Participation From Federated Learning Agents. - Jinlong Pang; Jiaheng Wei; Yifan Hua; Chen Qian 001; Yang Liu 018 (CoRR, 2025)