Saved in:
| Main Authors: | Kang, Zilin, Hu, Chenyuan, Luo, Yu, Yuan, Zhecheng, Zheng, Ruijie, Xu, Huazhe |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.02712 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Entropy Regularizing Activation: Boosting Continuous Control, Large Language Models, and Image Classification with Activation as Entropy Constraints
by: Kang, Zilin, et al.
Published: (2025)
by: Kang, Zilin, et al.
Published: (2025)
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
by: Xu, Guowei, et al.
Published: (2023)
by: Xu, Guowei, et al.
Published: (2023)
3D Diffusion Policy: Generalizable Visuomotor Policy Learning via Simple 3D Representations
by: Ze, Yanjie, et al.
Published: (2024)
by: Ze, Yanjie, et al.
Published: (2024)
TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning
by: Zheng, Ruijie, et al.
Published: (2023)
by: Zheng, Ruijie, et al.
Published: (2023)
Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization
by: Lei, Kun, et al.
Published: (2023)
by: Lei, Kun, et al.
Published: (2023)
Growing with Experience: Growing Neural Networks in Deep Reinforcement Learning
by: Fehring, Lukas, et al.
Published: (2025)
by: Fehring, Lukas, et al.
Published: (2025)
Model-Based Reinforcement Learning for Control of Strongly-Disturbed Unsteady Aerodynamic Flows
by: Liu, Zhecheng, et al.
Published: (2024)
by: Liu, Zhecheng, et al.
Published: (2024)
Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning
by: Ma, Guozheng, et al.
Published: (2025)
by: Ma, Guozheng, et al.
Published: (2025)
Continual Deep Reinforcement Learning to Prevent Catastrophic Forgetting in Jamming Mitigation
by: Davaslioglu, Kemal, et al.
Published: (2024)
by: Davaslioglu, Kemal, et al.
Published: (2024)
COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL
by: Wang, Xiyao, et al.
Published: (2023)
by: Wang, Xiyao, et al.
Published: (2023)
Understanding Generalization and Forgetting in In-Context Continual Learning
by: Li, Guangyu, et al.
Published: (2026)
by: Li, Guangyu, et al.
Published: (2026)
DittoGym: Learning to Control Soft Shape-Shifting Robots
by: Huang, Suning, et al.
Published: (2024)
by: Huang, Suning, et al.
Published: (2024)
Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning
by: Shi, Ruizhe, et al.
Published: (2023)
by: Shi, Ruizhe, et al.
Published: (2023)
Spurious Forgetting in Continual Learning of Language Models
by: Zheng, Junhao, et al.
Published: (2025)
by: Zheng, Junhao, et al.
Published: (2025)
Rethinking the Role of Dynamic Sparse Training for Scalable Deep Reinforcement Learning
by: Ma, Guozheng, et al.
Published: (2025)
by: Ma, Guozheng, et al.
Published: (2025)
Grow, Don't Overwrite: Fine-tuning Without Forgetting
by: Adila, Dyah, et al.
Published: (2026)
by: Adila, Dyah, et al.
Published: (2026)
On the Implicit Adversariality of Catastrophic Forgetting in Deep Continual Learning
by: Peng, Ze, et al.
Published: (2025)
by: Peng, Ze, et al.
Published: (2025)
Overcoming Catastrophic Forgetting in Visual Continual Learning with Reinforcement Fine-Tuning
by: Lou, Meng, et al.
Published: (2026)
by: Lou, Meng, et al.
Published: (2026)
Retrofit: Continual Learning with Controlled Forgetting for Binary Security Detection and Analysis
by: He, Yiling, et al.
Published: (2025)
by: He, Yiling, et al.
Published: (2025)
Understanding Forgetting in Continual Learning with Linear Regression
by: Ding, Meng, et al.
Published: (2024)
by: Ding, Meng, et al.
Published: (2024)
Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL
by: Luo, Yu, et al.
Published: (2024)
by: Luo, Yu, et al.
Published: (2024)
ACE : Off-Policy Actor-Critic with Causality-Aware Entropy Regularization
by: Ji, Tianying, et al.
Published: (2024)
by: Ji, Tianying, et al.
Published: (2024)
Continuous Limits of Coupled Flows in Representation Learning
by: Li, Zilin, et al.
Published: (2026)
by: Li, Zilin, et al.
Published: (2026)
Forget Forgetting: Continual Learning in a World of Abundant Memory
by: Cho, Dongkyu, et al.
Published: (2025)
by: Cho, Dongkyu, et al.
Published: (2025)
FOREVER: Forgetting Curve-Inspired Memory Replay for Language Model Continual Learning
by: Feng, Yujie, et al.
Published: (2026)
by: Feng, Yujie, et al.
Published: (2026)
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
by: Wang, Zhenyi, et al.
Published: (2023)
by: Wang, Zhenyi, et al.
Published: (2023)
GenSim: Generating Robotic Simulation Tasks via Large Language Models
by: Wang, Lirui, et al.
Published: (2023)
by: Wang, Lirui, et al.
Published: (2023)
TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning
by: Wu, Jinyang, et al.
Published: (2025)
by: Wu, Jinyang, et al.
Published: (2025)
Efficient Reinforcement Learning via Decoupling Exploration and Utilization
by: Yang, Jingpu, et al.
Published: (2023)
by: Yang, Jingpu, et al.
Published: (2023)
From Order to Distribution: A Spectral Characterization of Forgetting in Continual Learning
by: Xu, Zonghuan, et al.
Published: (2026)
by: Xu, Zonghuan, et al.
Published: (2026)
Deep Reinforcement Learning for Efficient and Fair Allocation of Health Care Resources
by: Li, Yikuan, et al.
Published: (2023)
by: Li, Yikuan, et al.
Published: (2023)
Do Neural Operators Forget Geometry? The Forgetting Hypothesis in Deep Operator Learning
by: Xia, Yanming, et al.
Published: (2026)
by: Xia, Yanming, et al.
Published: (2026)
Fisher-Guided Selective Forgetting: Mitigating The Primacy Bias in Deep Reinforcement Learning
by: Falzari, Massimiliano, et al.
Published: (2025)
by: Falzari, Massimiliano, et al.
Published: (2025)
Failure-Aware RL: Reliable Offline-to-Online Reinforcement Learning with Self-Recovery for Real-World Manipulation
by: Li, Huanyu, et al.
Published: (2026)
by: Li, Huanyu, et al.
Published: (2026)
Model Zoo: A Growing "Brain" That Learns Continually
by: Ramesh, Rahul, et al.
Published: (2021)
by: Ramesh, Rahul, et al.
Published: (2021)
RULE: Reinforcement UnLEarning Achieves Forget-Retain Pareto Optimality
by: Zhang, Chenlong, et al.
Published: (2025)
by: Zhang, Chenlong, et al.
Published: (2025)
No Forgetting Learning: Buffer-free Continual Learning Classification
by: Vahedifar, Mohammad Ali, et al.
Published: (2025)
by: Vahedifar, Mohammad Ali, et al.
Published: (2025)
Overcoming Growth-Induced Forgetting in Task-Agnostic Continual Learning
by: Zhao, Yuqing, et al.
Published: (2024)
by: Zhao, Yuqing, et al.
Published: (2024)
MENTOR: Mixture-of-Experts Network with Task-Oriented Perturbation for Visual Reinforcement Learning
by: Huang, Suning, et al.
Published: (2024)
by: Huang, Suning, et al.
Published: (2024)
OMPO: A Unified Framework for RL under Policy and Dynamics Shifts
by: Luo, Yu, et al.
Published: (2024)
by: Luo, Yu, et al.
Published: (2024)
Similar Items
-
Entropy Regularizing Activation: Boosting Continuous Control, Large Language Models, and Image Classification with Activation as Entropy Constraints
by: Kang, Zilin, et al.
Published: (2025) -
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
by: Xu, Guowei, et al.
Published: (2023) -
3D Diffusion Policy: Generalizable Visuomotor Policy Learning via Simple 3D Representations
by: Ze, Yanjie, et al.
Published: (2024) -
TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning
by: Zheng, Ruijie, et al.
Published: (2023) -
Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization
by: Lei, Kun, et al.
Published: (2023)