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Found 3 papers, 1 papers with code
Exemplar-Free Class Incremental Learning via Incremental Representation
Exemplar-Free Class Incremental Learning (efCIL) aims to continuously incorporate the knowledge from new classes while retaining previously learned information, without storing any old-class exemplars (i. e., samples).
CLIP-KD: An Empirical Study of Distilling CLIP Models
CLIP has become a promising language-supervised visual pre-training framework and achieves excellent performance over a wide range of tasks.
Categories of Response-Based, Feature-Based, and Relation-Based Knowledge Distillation
Knowledge Distillation (KD) aims to optimize a lightweight network from the perspective of over-parameterized training.
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