MAIL constructs modality-aware ID-free identities via dynamic positional encoding modulation and applies counterfactual structure learning with popularity penalization, yielding 7.81% Recall@10 and 12.81% NDCG@10 gains on five Amazon datasets.
Dualgnn: Dual graph neural network for multimedia recommendation
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
FDQ improves stability in multimodal graph unlearning by using feature-dimension aware quantile selection to protect sensitive high-dimensional layers while preserving utility and enabling effective forgetting.
citing papers explorer
-
Modality-Aware Identity Construction and Counterfactual Structure Learning for ID-Free Multimodal Recommendation
MAIL constructs modality-aware ID-free identities via dynamic positional encoding modulation and applies counterfactual structure learning with popularity penalization, yielding 7.81% Recall@10 and 12.81% NDCG@10 gains on five Amazon datasets.
-
Stable Multimodal Graph Unlearning via Feature-Dimension Aware Quantile Selection
FDQ improves stability in multimodal graph unlearning by using feature-dimension aware quantile selection to protect sensitive high-dimensional layers while preserving utility and enabling effective forgetting.