7 papers
The Sequential Price of Continual Learning
Zonghuan Xu, Xingjun Ma
Sequential task updates are fundamental to continual learning, but their recency bias can impose a lasting performance cost. We study this cost in an overparameterized linear-regre…
Hypothesis Testing with Conditional Queries: Learnability and the Value of Interaction
Zonghuan Xu
Model evaluations may fix all tests before observing any responses or select later tests using earlier responses. We study this choice in a conditional-query model on a finite outc…
Optimal Training-Time Scaling in Gradual Adaptation
Zonghuan Xu, Krishna Harish
In gradual adaptation, how should the training time on each task change as the number of intermediate tasks increases? We study this question for overparameterized linear regressio…
From Order to Distribution: An Exact Operator Framework for Forgetting in Continual Learning
Zonghuan Xu, Xingjun Ma
A central challenge in continual learning is forgetting: the loss of performance on previously learned tasks after learning new ones. Prior theory has analyzed forgetting under ran…
What Does a Sharing Question Add? Auditing LLM Survey Scores for Misinformation
Zonghuan Xu, Xiang Zheng, Yutao Wu +1
Evaluating misinformation requires distinguishing whether readers believe content from whether they would share it. Asking large language models (LLMs) both questions yields two sc…
AttackVLA: Benchmarking Adversarial and Backdoor Attacks on Vision-Language-Action Models
Jiayu Li, Yunhan Zhao, Xiang Zheng +4
Vision-Language-Action (VLA) models enable robots to interpret natural-language instructions and perform diverse tasks, yet their integration of perception, language, and control i…
DropVLA: An Action-Level Backdoor Attack on Vision-Language-Action Models
Zonghuan Xu, Jiayu Li, Yunhan Zhao +3
Vision-Language-Action (VLA) models map multimodal perception and language instructions to executable robot actions, making them particularly vulnerable to behavioral backdoor mani…