52 citations · 52 across the 4 of their papers we have counts for
4 papers
Repurposing Adversarial Perturbations for Continual Learning: From Defense to Active Alignment
Ran Liu, Min Yu, Mingqi Liu +7
In dynamic environments, large language models need to keep adapting to new tasks, but continual learning often suffers from forgetting, limited transfer, and vulnerability to adve…
SpeechForensics: Audio-Visual Speech Representation Learning for Face Forgery Detection
Yachao Liang, Min Yu, Gang Li +6
Detection of face forgery videos remains a formidable challenge in the field of digital forensics, especially the generalization to unseen datasets and common perturbations. In thi…
GLIMMER: Incorporating Graph and Lexical Features in Unsupervised Multi-Document Summarization
Ran Liu, Ming Liu, Min Yu +6
Pre-trained language models are increasingly being used in multi-document summarization tasks. However, these models need large-scale corpora for pre-training and are domain-depend…
Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networks
Qingsong Lv, Ming Ding, Qiang Liu +7
Heterogeneous graph neural networks (HGNNs) have been blossoming in recent years, but the unique data processing and evaluation setups used by each work obstruct a full understandi…