ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2407.12443
  4. Cited By
Preventing Catastrophic Overfitting in Fast Adversarial Training: A
  Bi-level Optimization Perspective

Preventing Catastrophic Overfitting in Fast Adversarial Training: A Bi-level Optimization Perspective

17 July 2024
Zhaoxin Wang
Handing Wang
Cong Tian
Yaochu Jin
    AAML
ArXivPDFHTML

Papers citing "Preventing Catastrophic Overfitting in Fast Adversarial Training: A Bi-level Optimization Perspective"

2 / 2 papers shown
Title
PR-Attack: Coordinated Prompt-RAG Attacks on Retrieval-Augmented Generation in Large Language Models via Bilevel Optimization
PR-Attack: Coordinated Prompt-RAG Attacks on Retrieval-Augmented Generation in Large Language Models via Bilevel Optimization
Yang Jiao
X. Wang
Kai Yang
AAML
SILM
31
0
0
10 Apr 2025
Make Some Noise: Reliable and Efficient Single-Step Adversarial Training
Make Some Noise: Reliable and Efficient Single-Step Adversarial Training
Pau de Jorge
Adel Bibi
Riccardo Volpi
Amartya Sanyal
Philip H. S. Torr
Grégory Rogez
P. Dokania
AAML
49
45
0
02 Feb 2022
1