3 papers
cs.LG2026
Spectral Collapse Drives Loss of Plasticity in Deep Continual Learning
Arjun Prakash, Naicheng He, Kaicheng Guo +5
We investigate why deep neural networks suffer from loss of plasticity in continual learning, and thus fail to learn new tasks without reinitializing parameters. We show that this…
cs.AI2026
Trust Your Memory: Verifiable Control of Smart Homes through Reinforcement Learning with Multi-dimensional Rewards
Kai-Yuan Guo, Jiang Wang, Renjie Zhao +5
Large Language Models (LLMs) have become a key foundation for enabling personalized smart home experiences. While existing studies have explored how smart home assistants understan…
cs.LG2025
Benchmarking Partial Observability in Reinforcement Learning with a Suite of Memory-Improvable Domains
Ruo Yu Tao, Kaicheng Guo, Cameron Allen +1
Mitigating partial observability is a necessary but challenging task for general reinforcement learning algorithms. To improve an algorithm's ability to mitigate partial observabil…