David Khachaturov

According to our database, David Khachaturov authored at least 12 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Human-Provenance Verification should be Treated as Labor Infrastructure in AI-Saturated Markets.

Erin McGurk, David Khachaturov

CoRR, May, 2026

Controllable and explainable personality sliders for LLMs at inference time.

Florian Hoppe, David Khachaturov, Robert Mullins, Mark Huasong Meng

CoRR, March, 2026

2025

Governments Should Mandate Tiered Anonymity on Social-Media Platforms to Counter Deepfakes and LLM-Driven Mass Misinformation.

David Khachaturov, Roxanne Schnyder, Robert Mullins

CoRR, June, 2025

Adversarial Suffix Filtering: a Defense Pipeline for LLMs.

David Khachaturov, Robert Mullins

CoRR, May, 2025

Watermarking Needs Input Repetition Masking.

David Khachaturov, Robert Mullins, Ilia Shumailov, Sumanth Dathathri

CoRR, April, 2025

"I am bad": Interpreting Stealthy, Universal and Robust Audio Jailbreaks in Audio-Language Models.

Isha Gupta, David Khachaturov, Robert Mullins

CoRR, February, 2025

Scaling Trends for Data Poisoning in LLMs.

Dillon Bowen, Brendan Murphy, Will Cai, David Khachaturov, Adam Gleave, Kellin Pelrine

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Complexity Matters: Effective Dimensionality as a Measure for Adversarial Robustness.

David Khachaturov, Robert Mullins

CoRR, 2024

Scaling Laws for Data Poisoning in LLMs.

Dillon Bowen, Brendan Murphy, Will Cai, David Khachaturov, Adam Gleave, Kellin Pelrine

CoRR, 2024

QBI: Quantile-based Bias Initialization for Efficient Private Data Reconstruction in Federated Learning.

Micha V. Nowak, Tim P. Bott, David Khachaturov, Frank Puppe, Adrian Krenzer, Amar Hekalo

CoRR, 2024

2023

Human-Producible Adversarial Examples.

David Khachaturov, Yue Gao, Ilia Shumailov, Robert Mullins, Ross J. Anderson, Kassem Fawaz

CoRR, 2023

2021

Markpainting: Adversarial Machine Learning meets Inpainting.

David Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, Ross J. Anderson

Proceedings of the 38th International Conference on Machine Learning, 2021