类增量学习 | Geeks_Z の Blog

类增量学习: Class-Incremental Learning

目录

# 1. Survey: 1-1. 增量学习综述 1-2. Continual Learning with Pre-Trained Models A Survey 1-3. Continual Learning for Large Language Models A Survey 1-4. Recent Advances of Foundation Language Models-based Continual Learning-A Survey 1-5. Continual Learning With Knowledge Distillation A Survey 1-6. Architecture Matters in Continual Learning

# 2. Direct Replay: 2-1. iCaRL 2-2. RM

# 3. Generative Replay: 3-1. DCMI

# 4. Data Regularization: 4-1. GBSS

# 5. Neuron Expansion: 5-1. PackNet

# 6. Backbone Expansion: 6-1. DER 6-2. FOSTER

# 7. PEFT Expansion: 7-1. L2P 7-2. DualPrompt 7-3. CODA-Prompt 7-4. PromptFusion 7-5. CPP 7-6. EASE 7-7. APER 7-8. InfLoRA 7-9. MoE-Adapters4CL 7-10. MOS 7-11. LAE 7-12. HiDe-Prompt 7-13. CPrompt 7-14. PILoRA

# 8. Parameter Regularization: 8-1. EWC 8-2. CoFiMA

# 9. Logit Distillation: 9-1. LwF 9-2. COIL

# 10. Feature Distillation: 10-1. LUCIR

# 11. Relational Distillation: 11-1. PRD

# 12. Feature Rectify: 12-1. FCS 12-2. SDC 12-3. RKR 12-4. FA 12-5. CCLL 12-6. RKR 12-7. ADC 12-8. DYSON

# 13. Logit Rectify: 13-1. BiC

# 14. Weight Rectify: 14-1. WA

# 15. Template-Based Classification: 15-1. RanPAC

# 16. Energy: 16-1. ELI 16-2. EA 16-3. ESN

上次更新: 2025/04/02, 12:03:38

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