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Found 4 papers, 1 papers with code
REBEL: A Regularization-Based Solution for Reward Overoptimization in Robotic Reinforcement Learning from Human Feedback
Current methods to mitigate this misalignment work by learning reward functions from human preferences; however, they inadvertently introduce a risk of reward overoptimization.
Pre-Trained Masked Image Model for Mobile Robot Navigation
2D top-down maps are commonly used for the navigation and exploration of mobile robots through unknown areas.
SeMask: Semantically Masked Transformers for Semantic Segmentation
To achieve this, we propose SeMask, a simple and effective framework that incorporates semantic information into the encoder with the help of a semantic attention operation.
Ranked #10 on
Semantic Segmentation
on Cityscapes val
OffRoadTranSeg: Semi-Supervised Segmentation using Transformers on OffRoad environments
We present OffRoadTranSeg, the first end-to-end framework for semi-supervised segmentation in unstructured outdoor environment using transformers and automatic data selection for labelling.
