3 accepted papers
To effectively manage the complexities of real-world dynamic environments, continual learning must incrementally acquire, update, and accumulate knowledge from a stream of tasks of different nature - without suffering from catastrophic forgetting of prior knowledge. While this capability is innate t
White-box targeted adversarial attacks reveal core vulnerabilities in Deep Neural Networks (DNNs), yet two key challenges persist: (i) How many target classes can be attacked simultaneously in a specified order, known as the *ordered top-$K$ attack* problem ($K \geq 1$)? (ii) How to compute the corr…
Fine-tuning large pretrained Transformer models can focus on either introducing a small number of new learnable parameters (parameter efficiency) or editing representations of a small number of tokens using lightweight modules (representation efficiency). While the pioneering method LoRA (Low-Rank A…