12 citations · 33 across the 6 of their papers we have counts for
6 papers
Mitigating Catastrophic Forgetting in Task-Incremental Continual Learning with Adaptive Classification Criterion
Yun Luo, Xiaotian Lin, Zhen Yang +3
Task-incremental continual learning refers to continually training a model in a sequence of tasks while overcoming the problem of catastrophic forgetting (CF). The issue arrives fo…
Investigating Forgetting in Pre-Trained Representations Through Continual Learning
Yun Luo, Zhen Yang, Xuefeng Bai +3
Representation forgetting refers to the drift of contextualized representations during continual training. Intuitively, the representation forgetting can influence the general know…
Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias
Zihan Liu, Yun Luo, Lirong Wu +2
It has become cognitive inertia to employ cross-entropy loss function in classification related tasks. In the untargeted attacks on graph structure, the gradients derived from the…
Improving (Dis)agreement Detection with Inductive Social Relation Information From Comment-Reply Interactions
Yun Luo, Zihan Liu, Stan Z. Li +1
(Dis)agreement detection aims to identify the authors' attitudes or positions (\textit{agree, disagree, neutral}) towards a specific text. It is limited for existing methods merely…
Mere Contrastive Learning for Cross-Domain Sentiment Analysis
Yun Luo, Fang Guo, Zihan Liu +1
Cross-domain sentiment analysis aims to predict the sentiment of texts in the target domain using the model trained on the source domain to cope with the scarcity of labeled data.…
Exploiting Sentiment and Common Sense for Zero-shot Stance Detection
Yun Luo, Zihan Liu, Yuefeng Shi +2
The stance detection task aims to classify the stance toward given documents and topics. Since the topics can be implicit in documents and unseen in training data for zero-shot set…