Search Results for author:
Found 5 papers, 0 papers with code
ROIC-DM: Robust Text Inference and Classification via Diffusion Model
While language models have made many milestones in text inference and classification tasks, they remain susceptible to adversarial attacks that can lead to unforeseen outcomes.
Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures
To reveal the real vulnerability of FedRecs, in this paper, we present a new poisoning attack method to manipulate target items' ranks and exposure rates effectively in the top-$K$ recommendation without relying on any prior knowledge.
Interaction-level Membership Inference Attack Against Federated Recommender Systems
An interaction-level membership inference attacker is first designed, and then the classical privacy protection mechanism, Local Differential Privacy (LDP), is adopted to defend against the membership inference attack.
Federated Unlearning for On-Device Recommendation
It removes a user's contribution by rolling back and calibrating the historical parameter updates and then uses these updates to speed up federated recommender reconstruction.
Unified Question Generation with Continual Lifelong Learning
To solve the problems, we propose a model named Unified-QG based on lifelong learning techniques, which can continually learn QG tasks across different datasets and formats.
