Jiaheng Wei

Orcid: 0000-0003-3573-1711

According to our database1, Jiaheng Wei authored at least 18 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Measuring and Reducing LLM Hallucination without Gold-Standard Answers via Expertise-Weighting.
CoRR, 2024

Human-Instruction-Free LLM Self-Alignment with Limited Samples.
CoRR, 2024

2023
Client-side Gradient Inversion Against Federated Learning from Poisoning.
CoRR, 2023

Do humans and machines have the same eyes? Human-machine perceptual differences on image classification.
CoRR, 2023

Fairness Improves Learning from Noisily Labeled Long-Tailed Data.
CoRR, 2023

To Aggregate or Not? Learning with Separate Noisy Labels.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Distributionally Robust Post-hoc Classifiers under Prior Shifts.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Auditing for Federated Learning: A Model Elicitation Approach.
Proceedings of the Fifth International Conference on Distributed Artificial Intelligence, 2023

2022
Consensus on Dynamic Stochastic Block Models: Fast Convergence and Phase Transitions.
CoRR, 2022

To Smooth or Not? When Label Smoothing Meets Noisy Labels.
Proceedings of the International Conference on Machine Learning, 2022

Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations.
Proceedings of the Tenth International Conference on Learning Representations, 2022

DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
Induced Domain Adaptation.
CoRR, 2021

Understanding (Generalized) Label Smoothing when Learning with Noisy Labels.
CoRR, 2021

PeerGAN: Generative Adversarial Networks with a Competing Peer Discriminator.
CoRR, 2021

When Optimizing f-Divergence is Robust with Label Noise.
Proceedings of the 9th International Conference on Learning Representations, 2021

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

2020
Incentives for Federated Learning: a Hypothesis Elicitation Approach.
CoRR, 2020


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