REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective
Fuente:
arXiv
Saved in:
| Main Authors: | Geisler, Simon, Wollschläger, Tom, Abdalla, M. H. I., Cohen-Addad, Vincent, Gasteiger, Johannes, Günnemann, Stephan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Attacking Large Language Models with Projected Gradient Descent
by: Geisler, Simon, et al.
Published: (2024)
by: Geisler, Simon, et al.
Published: (2024)
The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence
by: Wollschläger, Tom, et al.
Published: (2025)
by: Wollschläger, Tom, et al.
Published: (2025)
GemNet: Universal Directional Graph Neural Networks for Molecules
by: Gasteiger, Johannes, et al.
Published: (2021)
by: Gasteiger, Johannes, et al.
Published: (2021)
Adversarial Alignment for LLMs Requires Simpler, Reproducible, and More Measurable Objectives
by: Schwinn, Leo, et al.
Published: (2025)
by: Schwinn, Leo, et al.
Published: (2025)
Sampling-aware Adversarial Attacks Against Large Language Models
by: Beyer, Tim, et al.
Published: (2025)
by: Beyer, Tim, et al.
Published: (2025)
What Expressivity Theory Misses: Message Passing Complexity for GNNs
by: Kemper, Niklas, et al.
Published: (2025)
by: Kemper, Niklas, et al.
Published: (2025)
Energy-based Epistemic Uncertainty for Graph Neural Networks
by: Fuchsgruber, Dominik, et al.
Published: (2024)
by: Fuchsgruber, Dominik, et al.
Published: (2024)
Adversarial Robustness of Graph Transformers
by: Foth, Philipp, et al.
Published: (2024)
by: Foth, Philipp, et al.
Published: (2024)
Diffusion LLMs are Natural Adversaries for any LLM
by: Lüdke, David, et al.
Published: (2025)
by: Lüdke, David, et al.
Published: (2025)
Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory
by: Fuchsgruber, Dominik, et al.
Published: (2025)
by: Fuchsgruber, Dominik, et al.
Published: (2025)
Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness
by: Campi, Francesco, et al.
Published: (2023)
by: Campi, Francesco, et al.
Published: (2023)
Using Mechanistic Interpretability to Craft Adversarial Attacks against Large Language Models
by: Winninger, Thomas, et al.
Published: (2025)
by: Winninger, Thomas, et al.
Published: (2025)
Adversarial Attacks on Graph Neural Networks via Meta Learning
by: Zügner, Daniel, et al.
Published: (2019)
by: Zügner, Daniel, et al.
Published: (2019)
Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance
by: Fuchsgruber, Dominik, et al.
Published: (2024)
by: Fuchsgruber, Dominik, et al.
Published: (2024)
The Illusion of Certainty: Uncertainty Quantification for LLMs Fails under Ambiguity
by: Tomov, Tim, et al.
Published: (2025)
by: Tomov, Tim, et al.
Published: (2025)
Long-Range Graph Wavelet Networks
by: Guerranti, Filippo, et al.
Published: (2025)
by: Guerranti, Filippo, et al.
Published: (2025)
SAFT: Structure-Aware Fine-Tuning of LLMs for AMR-to-Text Generation
by: Kamel, Rafiq, et al.
Published: (2025)
by: Kamel, Rafiq, et al.
Published: (2025)
Spatio-Spectral Graph Neural Networks
by: Geisler, Simon, et al.
Published: (2024)
by: Geisler, Simon, et al.
Published: (2024)
Localized Randomized Smoothing for Collective Robustness Certification
by: Schuchardt, Jan, et al.
Published: (2022)
by: Schuchardt, Jan, et al.
Published: (2022)
Uncertainty for Active Learning on Graphs
by: Fuchsgruber, Dominik, et al.
Published: (2024)
by: Fuchsgruber, Dominik, et al.
Published: (2024)
Expressivity and Generalization: Fragment-Biases for Molecular GNNs
by: Wollschläger, Tom, et al.
Published: (2024)
by: Wollschläger, Tom, et al.
Published: (2024)
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks
by: Scholten, Yan, et al.
Published: (2023)
by: Scholten, Yan, et al.
Published: (2023)
Efficient Adversarial Training in LLMs with Continuous Attacks
by: Xhonneux, Sophie, et al.
Published: (2024)
by: Xhonneux, Sophie, et al.
Published: (2024)
Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space
by: Ketata, Mohamed Amine, et al.
Published: (2024)
by: Ketata, Mohamed Amine, et al.
Published: (2024)
Certifiably Robust Encoding Schemes
by: Saxena, Aman, et al.
Published: (2024)
by: Saxena, Aman, et al.
Published: (2024)
Discrete Randomized Smoothing Meets Quantum Computing
by: Wollschläger, Tom, et al.
Published: (2024)
by: Wollschläger, Tom, et al.
Published: (2024)
Explainable Graph Neural Networks Under Fire
by: Li, Zhong, et al.
Published: (2024)
by: Li, Zhong, et al.
Published: (2024)
A Probabilistic Perspective on Unlearning and Alignment for Large Language Models
by: Scholten, Yan, et al.
Published: (2024)
by: Scholten, Yan, et al.
Published: (2024)
Retriever Portfolios: A Principled Approach to Adaptive RAG
by: Stouras, Miltiadis, et al.
Published: (2026)
by: Stouras, Miltiadis, et al.
Published: (2026)
REINFORCE-ING Chemical Language Models for Drug Discovery
by: Thomas, Morgan, et al.
Published: (2025)
by: Thomas, Morgan, et al.
Published: (2025)
Closing the Distribution Gap in Adversarial Training for LLMs
by: Hu, Chengzhi, et al.
Published: (2026)
by: Hu, Chengzhi, et al.
Published: (2026)
SYNAPSE-G: Bridging Large Language Models and Graph Learning for Rare Event Classification
by: Tavakkol, Sasan, et al.
Published: (2025)
by: Tavakkol, Sasan, et al.
Published: (2025)
Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More
by: Schuchardt, Jan, et al.
Published: (2023)
by: Schuchardt, Jan, et al.
Published: (2023)
Less is More: Adaptive Coverage for Synthetic Training Data
by: Tavakkol, Sasan, et al.
Published: (2025)
by: Tavakkol, Sasan, et al.
Published: (2025)
QuantFactor REINFORCE: Mining Steady Formulaic Alpha Factors with Variance-bounded REINFORCE
by: Zhao, Junjie, et al.
Published: (2024)
by: Zhao, Junjie, et al.
Published: (2024)
Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks
by: Gosch, Lukas, et al.
Published: (2024)
by: Gosch, Lukas, et al.
Published: (2024)
Multi-Swap $k$-Means++
by: Beretta, Lorenzo, et al.
Published: (2023)
by: Beretta, Lorenzo, et al.
Published: (2023)
Efficient Data Selection at Scale via Influence Distillation
by: Nikdan, Mahdi, et al.
Published: (2025)
by: Nikdan, Mahdi, et al.
Published: (2025)
Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning
by: Scholten, Yan, et al.
Published: (2024)
by: Scholten, Yan, et al.
Published: (2024)
Multi-View Stochastic Block Models
by: Cohen-Addad, Vincent, et al.
Published: (2024)
by: Cohen-Addad, Vincent, et al.
Published: (2024)
Similar Items
-
Attacking Large Language Models with Projected Gradient Descent
by: Geisler, Simon, et al.
Published: (2024) -
The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence
by: Wollschläger, Tom, et al.
Published: (2025) -
GemNet: Universal Directional Graph Neural Networks for Molecules
by: Gasteiger, Johannes, et al.
Published: (2021) -
Adversarial Alignment for LLMs Requires Simpler, Reproducible, and More Measurable Objectives
by: Schwinn, Leo, et al.
Published: (2025) -
Sampling-aware Adversarial Attacks Against Large Language Models
by: Beyer, Tim, et al.
Published: (2025)