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Found 4 papers, 2 papers with code
Unleashing the Potential of Text-attributed Graphs: Automatic Relation Decomposition via Large Language Models
Recent advancements in text-attributed graphs (TAGs) have significantly improved the quality of node features by using the textual modeling capabilities of language models.
NOTE: Robust Continual Test-time Adaptation Against Temporal Correlation
Test-time adaptation (TTA) is an emerging paradigm that addresses distributional shifts between training and testing phases without additional data acquisition or labeling cost; only unlabeled test data streams are used for continual model adaptation.
Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion Modeling
Instance-aware segmentation of unseen objects is essential for a robotic system in an unstructured environment.
Acceleration of Actor-Critic Deep Reinforcement Learning for Visual Grasping in Clutter by State Representation Learning Based on Disentanglement of a Raw Input Image
For a robotic grasping task in which diverse unseen target objects exist in a cluttered environment, some deep learning-based methods have achieved state-of-the-art results using visual input directly.
