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Found 7 papers, 3 papers with code
Training a Vision Language Model as Smartphone Assistant
Addressing the challenge of a digital assistant capable of executing a wide array of user tasks, our research focuses on the realm of instruction-based mobile device control.
Improving Deep Dynamics Models for Autonomous Vehicles with Multimodal Latent Mapping of Surfaces
By training everything end-to-end with the loss of the dynamics model, we enforce the latent mapper to learn an update rule for the latent map that is useful for the subsequent dynamics model.
Dynamic Update-to-Data Ratio: Minimizing World Model Overfitting
Early stopping based on the validation set performance is a popular approach to find the right balance between under- and overfitting in the context of supervised learning.
Model-based Reinforcement Learning
reinforcement-learning
+1
Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning
Accurate value estimates are important for off-policy reinforcement learning.
Modality-Buffet for Real-Time Object Detection
Real-time object detection in videos using lightweight hardware is a crucial component of many robotic tasks.
Scaling Imitation Learning in Minecraft
Imitation learning is a powerful family of techniques for learning sensorimotor coordination in immersive environments.
Scheduled Intrinsic Drive: A Hierarchical Take on Intrinsically Motivated Exploration
Many state-of-the-art methods use intrinsic motivation to complement the sparse extrinsic reward signal, giving the agent more opportunities to receive feedback during exploration.
