CoDCL combines counterfactual data augmentation with contrastive learning as a universal module to improve temporal link prediction in social networks.
Social recommendation via graph-level counterfactual aug- mentation.Proceedings of the AAAI Conference on Ar- tificial Intelligence, 39(1):334–342, Apr
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
CoDCL: Counterfactual-Inspired Augmentation Contrastive Learning for Temporal Link Prediction in Social Networks
CoDCL combines counterfactual data augmentation with contrastive learning as a universal module to improve temporal link prediction in social networks.