3 papers
cs.AI2026
Causally Robust Reward Learning from Reason-Augmented Preference Feedback
Minjune Hwang, Yigit Korkmaz, Daniel Seita +1
Preference-based reward learning is widely used for shaping agent behavior to match a user's preference, yet its sparse binary feedback makes it especially vulnerable to causal con…
cs.LG2025
Actor-Free Continuous Control via Structurally Maximizable Q-Functions
Yigit Korkmaz, Urvi Bhuwania, Ayush Jain +1
Value-based algorithms are a cornerstone of off-policy reinforcement learning due to their simplicity and training stability. However, their use has traditionally been restricted t…
cs.RO2025
MILE: Model-based Intervention Learning
Yigit Korkmaz, Erdem Bıyık
Imitation learning techniques have been shown to be highly effective in real-world control scenarios, such as robotics. However, these approaches not only suffer from compounding e…