Entity interference from new knowledge graph entities causes up to 25% overestimation of CKGE method performance by disrupting prior predictions, requiring a corrected evaluation protocol.
Sentence embedding alignment for lifelong relation extraction, in: Burstein, J., Doran, C., Solorio, T
2 Pith papers cite this work. Polarity classification is still indexing.
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AdvCL repurposes adversarial perturbations into geometric control signals for continual learning using Intra-Smooth, Proto-Clip, and Inter-Align modules, reporting gains in performance, robustness, lower forgetting, and stronger transfer.
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Revisiting Catastrophic Forgetting in Continual Knowledge Graph Embedding
Entity interference from new knowledge graph entities causes up to 25% overestimation of CKGE method performance by disrupting prior predictions, requiring a corrected evaluation protocol.
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Repurposing Adversarial Perturbations for Continual Learning: From Defense to Active Alignment
AdvCL repurposes adversarial perturbations into geometric control signals for continual learning using Intra-Smooth, Proto-Clip, and Inter-Align modules, reporting gains in performance, robustness, lower forgetting, and stronger transfer.