activity
20242026
most citedEfficient Robot Design with Multi-Objective Black-Box Optimization and Large Language Models

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

collaborators

5 papers

cs.RO2026

Dexterous grasp data augmentation based on grasp synthesis with fingertip workspace cloud and contact-aware sampling

Liqi Wu, Haoyu Jia, Kento Kawaharazuka +2

Robotic grasping is a fundamental yet crucial component of robotic applications, as effective grasping often serves as the starting point for various tasks. With the rapid advancem…

cs.RO20261 cited

Efficient Robot Design with Multi-Objective Black-Box Optimization and Large Language Models

Kento Kawaharazuka, Yoshiki Obinata, Naoaki Kanazawa +2

Various methods for robot design optimization have been developed so far. These methods are diverse, ranging from numerical optimization to black-box optimization. While numerical…

cs.AI2026

Toward Formalizing LLM-Based Agent Designs through Structural Context Modeling and Semantic Dynamics Analysis

Haoyu Jia, Kento Kawaharazuka, Kei Okada

Current research on large language model (LLM) agents is fragmented: discussions of conceptual frameworks and methodological principles are frequently intertwined with low-level im…

cs.LG2025

Mockingbird: How does LLM perform in general machine learning tasks?

Haoyu Jia, Yoshiki Obinata, Kento Kawaharazuka +1

Large language models (LLMs) are now being used with increasing frequency as chat bots, tasked with the summarizing information or generating text and code in accordance with user…

cs.RO2024

Remote Life Support Robot Interface System for Global Task Planning and Local Action Expansion Using Foundation Models

Yoshiki Obinata, Haoyu Jia, Kento Kawaharazuka +2

Robot systems capable of executing tasks based on language instructions have been actively researched. It is challenging to convey uncertain information that can only be determined…