Overcoming Catastrophic Forgetting in Visual Continual Learning with Reinforcement Fine-Tuning
cs.CV, cs.LG
Submitted: 2026-05-10
Updated: 2026-10-11
Code: https://github.com/LMMMEng/RaPO
Terminology
Sources
- Kimi k1.5: Scaling Reinforcement Learning with LLMs
- Qwen3-VL Technical Report
- Seed1.5-VL Technical Report
- Qwen3.5-Omni Technical Report
- A Survey of Reinforcement Learning for Large Reasoning Models
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models
- Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training
- Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
- OpenAI o1 System Card
- Proximal Policy Optimization Algorithms
- DAPO: An Open-Source LLM Reinforcement Learning System at Scale
- Group Sequence Policy Optimization
- Learning beyond Teacher: Generalized On-Policy Distillation with Reward Extrapolation
- Qwen3 Technical Report
- UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
- The Kinetics Human Action Video Dataset
- Soft Adaptive Policy Optimization
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