3 papers
cs.CL2025
Same Question, Different Words: A Latent Adversarial Framework for Prompt Robustness
Tingchen Fu, Fazl Barez
Insensitivity to semantically-preserving variations of prompts (paraphrases) is crucial for reliable behavior and real-world deployment of large language models. However, language…
cs.LG2025
Open Problems in Machine Unlearning for AI Safety
Fazl Barez, Tingchen Fu, Ameya Prabhu +16
As AI systems become more capable, widely deployed, and increasingly autonomous in critical areas such as cybersecurity, biological research, and healthcare, ensuring their safety…
cs.CR2024
PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
Tingchen Fu, Mrinank Sharma, Philip Torr +3
Preference learning is a central component for aligning current LLMs, but this process can be vulnerable to data poisoning attacks. To address this concern, we introduce PoisonBenc…