Shaopeng Fu

Orcid: 0009-0001-7522-8304

According to our database1, Shaopeng Fu authored at least 18 papers between 2020 and 2026.

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

2026
Benign Overfitting in Adversarial Training for Vision Transformers.
CoRR, April, 2026

Understanding and Improving Continuous Adversarial Training for LLMs via In-context Learning Theory.
CoRR, April, 2026

RefineRL: Advancing Competitive Programming with Self-Refinement Reinforcement Learning.
CoRR, April, 2026

Accelerating Suffix Jailbreak attacks with Prefix-Shared KV-cache.
CoRR, March, 2026

Understanding the Impact of Differentially Private Training on Memorization of Long-Tailed Data.
CoRR, February, 2026

Concept-Based Dictionary Learning for Inference-Time Safety in Vision Language Action Models.
CoRR, February, 2026

2025
Understanding Private Learning From Feature Perspective.
CoRR, November, 2025

C<sup>2</sup> ATTACK: Towards Representation Backdoor on CLIP via Concept Confusion.
CoRR, March, 2025

"Short-length" Adversarial Training Helps LLMs Defend "Long-length" Jailbreak Attacks: Theoretical and Empirical Evidence.
CoRR, February, 2025

2024
Low-carbon building evaluation index system based on hierarchical analysis method.
J. Comput. Methods Sci. Eng., 2024

Pre-trained Encoder Inference: Revealing Upstream Encoders In Downstream Machine Learning Services.
CoRR, 2024

Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2022
Robust Unlearnable Examples: Protecting Data Against Adversarial Learning.
CoRR, 2022

Knowledge Removal in Sampling-based Bayesian Inference.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Robust Unlearnable Examples: Protecting Data Privacy Against Adversarial Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting.
Neural Comput., 2021

Bayesian Inference Forgetting.
CoRR, 2021

2020
Robustness, Privacy, and Generalization of Adversarial Training.
CoRR, 2020


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