3 papers
cs.AI2025
A-LAMP: Agentic LLM-Based Framework for Automated MDP Modeling and Policy Generation
Hong Je-Gal, Chan-Bin Yi, Hyun-Suk Lee
Applying reinforcement learning (RL) to real-world tasks requires converting informal descriptions into a formal Markov decision process (MDP), implementing an executable environme…
cs.LG2025
POEM: Explore Unexplored Reliable Samples to Enhance Test-Time Adaptation
Chang'an Yi, Xiaohui Deng, Shuaicheng Niu +1
Test-time adaptation (TTA) aims to transfer knowledge from a source model to unknown test data with potential distribution shifts in an online manner. Many existing TTA methods rel…
cs.CV2025
When Small Guides Large: Cross-Model Co-Learning for Test-Time Adaptation
Chang'an Yi, Xiaohui Deng, Guohao Chen +3
Test-time Adaptation (TTA) adapts a given model to testing domain data with potential domain shifts through online unsupervised learning, yielding impressive performance. However,…