2 papers
cs.LG2026
Bounded Ratio Reinforcement Learning
Yunke Ao, Le Chen, Bruce D. Lee +5
Proximal Policy Optimization (PPO) has become the predominant algorithm for on-policy reinforcement learning due to its scalability and empirical robustness across domains. However…
cs.CV2025
Time-Contrastive Pretraining for In-Context Image and Video Segmentation
Assefa Wahd, Jacob Jaremko, Abhilash Hareendranathan
In-context learning (ICL) enables generalization to new tasks with minimal labeled data. However, mainstream ICL approaches rely on a gridding strategy, which lacks the flexibility…