knowledge retention
The capability of a machine learning model to retain and effectively utilize learned information when responding to new tasks or data, important for transfer learning.
- Confusion-Driven Self-Supervised Progressively Weighted Ensemble Learning for Non-Exemplar Class Incremental Learning
- DAA: Amplifying Unknown Discrepancy for Test-Time Discovery
- Data Efficient Adaptation in Large Language Models via Continuous Low-Rank Fine-Tuning
- Model Inversion with Layer-Specific Modeling and Alignment for Data-Free Continual Learning
- Online Functional Tensor Decomposition via Continual Learning for Streaming Data Completion
- Unveiling Concept Attribution in Diffusion Models