Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source
Hierarchical intertwined graph representation learning for skeleton-based action recognition. [PDF]
Zhang X, Tan C, Yuan Y, Yan J.
europepmc +1 more source
iHerd: an integrative hierarchical graph representation learning framework to quantify network changes and prioritize risk genes in disease. [PDF]
Duan Z +8 more
europepmc +1 more source
Asymmetry in Skipping Enhances Viability Against Control Input Noise
Quadruped animals use asymmetric galloping gaits at high speeds, yet the functional role of this asymmetry remains unclear. This study shows that left–right asymmetry in touchdown angles enhances robustness to control noise. Using a simple two‐legged locomotion model and viability theory, it demonstrates that asymmetric skipping substantially enlarges ...
Yuichi Ambe, Alvin So, Shinya Aoi
wiley +1 more source
Enhancing drug-target interaction prediction with graph representation learning and knowledge-based regularization. [PDF]
Yao Q, Chen Z, Cao Y, Hu H.
europepmc +1 more source
Auditory–Tactile Congruence for Synthesis of Adaptive Pain Expressions in RoboPatients
In this work, we explore auditory–tactile congruence for synthesizing adaptive vocal pain expressions in robopatients. Using a robopatient platform that integrates vocal pain sounds with palpation forces, we conducted 7680 trials across 20 participants.
Saitarun Nadipineni +4 more
wiley +1 more source
Identifying nutraceutical targets to treat polycystic ovary syndrome using graph representation learning. [PDF]
Hanassab S +10 more
europepmc +1 more source
Multimodal Engagement Assessment in Children During Invented Story Paradigm With a Social Robot
A multimodal framework is proposed to assess children's engagement during storytelling interactions with a social robot. Gaze, physiological, and behavioral data are combined and validated against observer ratings. An automated gaze‐labeling strategy is introduced, and supervised classifiers achieve high accuracy. The study supports scalable engagement
Laura Fiorini +7 more
wiley +1 more source
A Multisource Transformer-Guided Graph Representation Learning Framework for circRNA-Disease Association Prediction. [PDF]
Liang SZ, Wang L, You ZH, Yu CQ.
europepmc +1 more source
This study explores how information processing is distributed between brains and bodies through a codesign approach. Using the “backpropagation through soft body” framework, brain–body coupling agents are developed and analyzed across several tasks in which output is generated through the agents’ physical dynamics.
Hiroki Tomioka +3 more
wiley +1 more source

