22 citations · 37 across the 28 of their papers we have counts for
6 papers · 2 filters
Automata Extraction from Transformers
Yihao Zhang, Zeming Wei, Meng Sun
In modern machine (ML) learning systems, Transformer-based architectures have achieved milestone success across a broad spectrum of tasks, yet understanding their operational mecha…
A Theoretical Understanding of Self-Correction through In-context Alignment
Yifei Wang, Yuyang Wu, Zeming Wei +2
Going beyond mimicking limited human experiences, recent studies show initial evidence that, like humans, large language models (LLMs) are capable of improving their abilities pure…
Boosting Jailbreak Attack with Momentum
Yihao Zhang, Zeming Wei
Large Language Models (LLMs) have achieved remarkable success across diverse tasks, yet they remain vulnerable to adversarial attacks, notably the well-known jailbreak attack. In p…
Adversarial Representation Engineering: A General Model Editing Framework for Large Language Models
Yihao Zhang, Zeming Wei, Jun Sun +1
Since the rapid development of Large Language Models (LLMs) has achieved remarkable success, understanding and rectifying their internal complex mechanisms has become an urgent iss…
On the Duality Between Sharpness-Aware Minimization and Adversarial Training
Yihao Zhang, Hangzhou He, Jingyu Zhu +3
Adversarial Training (AT), which adversarially perturb the input samples during training, has been acknowledged as one of the most effective defenses against adversarial attacks, y…
Fight Back Against Jailbreaking via Prompt Adversarial Tuning
Yichuan Mo, Yuji Wang, Zeming Wei +1
While Large Language Models (LLMs) have achieved tremendous success in various applications, they are also susceptible to jailbreaking attacks. Several primary defense strategies h…