most citedMulti-task real-robot data with gaze attention for dual-arm fine manipulation

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.NE20241 cited

Training Spiking Neural Networks via Augmented Direct Feedback Alignment

Yongbo Zhang, Katsuma Inoue, Mitsumasa Nakajima +3

Spiking neural networks (SNNs), the models inspired by the mechanisms of real neurons in the brain, transmit and represent information by employing discrete action potentials or sp…

cs.RO2024

Informational Embodiment: Computational role of information structure in codes and robots

Alexandre Pitti, Kohei Nakajima, Yasuo Kuniyoshi

The body morphology plays an important role in the way information is perceived and processed by an agent. We address an information theory (IT) account on how the precision of sen…

cs.AI2024

Assessing the Aesthetic Evaluation Capabilities of GPT-4 with Vision: Insights from Group and Individual Assessments

Yoshia Abe, Tatsuya Daikoku, Yasuo Kuniyoshi

Recently, it has been recognized that large language models demonstrate high performance on various intellectual tasks. However, few studies have investigated alignment with humans…

cs.RO20241 cited

Multi-task real-robot data with gaze attention for dual-arm fine manipulation

Heecheol Kim, Yoshiyuki Ohmura, Yasuo Kuniyoshi

In the field of robotic manipulation, deep imitation learning is recognized as a promising approach for acquiring manipulation skills. Additionally, learning from diverse robot dat…

cs.CV2023

Ablation Study to Clarify the Mechanism of Object Segmentation in Multi-Object Representation Learning

Takayuki Komatsu, Yoshiyuki Ohmura, Yasuo Kuniyoshi

Multi-object representation learning aims to represent complex real-world visual input using the composition of multiple objects. Representation learning methods have often used un…