Establishes that no defense works against linear-proportion poisoning with unbounded noise in regularization-based continual learning and proposes verification and robust defenses for infrequent or bounded attacks.
Attack strength vs
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Framework uses LLaVA for triplet generation and two-stage fine-tuning to enhance composed fashion image retrieval.
citing papers explorer
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Theory of Continual Learning Against Data Poisoning Attacks
Establishes that no defense works against linear-proportion poisoning with unbounded noise in regularization-based continual learning and proposes verification and robust defenses for infrequent or bounded attacks.
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Exploring Multi-Modal Large Language Models and Two-Stage Fine-Tuning for Fashion Image Retrieval
Framework uses LLaVA for triplet generation and two-stage fine-tuning to enhance composed fashion image retrieval.