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Found 6 papers, 1 papers with code
ActiveNeuS: Active 3D Reconstruction using Neural Implicit Surface Uncertainty
Active learning in 3D scene reconstruction has been widely studied, as selecting informative training views is critical for the reconstruction.
Pearl: A Review-driven Persona-Knowledge Grounded Conversational Recommendation Dataset
Our experimental results demonstrate that utterances in PEARL include more specific user preferences, show expertise in the target domain, and provide recommendations more relevant to the dialogue context than those in prior datasets.
EXOT: Exit-aware Object Tracker for Safe Robotic Manipulation of Moving Object
We evaluate our method on the first-person video benchmark dataset, TREK-150, and on the custom dataset, RMOT-223, that we collect from the UR5e robot.
Robust Imitation via Mirror Descent Inverse Reinforcement Learning
Recently, adversarial imitation learning has shown a scalable reward acquisition method for inverse reinforcement learning (IRL) problems.
Unbiased learning with State-Conditioned Rewards in Adversarial Imitation Learning
The formulation draws a strong connection between adversarial learning and energy-based reinforcement learning; thus, the architecture is capable of recovering a reward function that induces a multi-modal policy.
Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning
Active learning is widely used to reduce labeling effort and training time by repeatedly querying only the most beneficial samples from unlabeled data.
