Results 211 to 220 of about 778,905 (302)

Multi-Entity-Topic Models with Who-entities and Where-entities

JSAI Technical Report, Type 2 SIG, 2007
SHIOZAKI, Hitohiro, EGUCHI, Koji, OHKAWA, Takenao   +2 more
openaire   +1 more source

The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?

Advanced Robotics Research, EarlyView.
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley   +1 more source

Detecting temporal clinical change in sequential chest radiography reports: a multi-model and multi-prompt evaluation of large language models. [PDF]

Front Digit Health
Erdağı E.
europepmc   +1 more source

Echinoderm‐Inspired Autonomy for Soft‐Legged Robots

Advanced Robotics Research, EarlyView.
Inspired by echinoderms, a modular soft robot achieves autonomous phototaxis without a central controller or explicit communication. Each limb independently adapts its actuation timing through local sensing and short‐term memory. Coordination emerges purely from physical interactions, demonstrating resilience to changes in morphology, environment, and ...
Harmannus A. H. Schomaker, Jelle de Vries, Johannes T. B. overvelde   +2 more
wiley   +1 more source

Stoic: fast and accurate protein stoichiometry prediction. [PDF]

Bioinformatics
Litvinov D, Pantolini L, Škrinjar P, Tauriello G, McCafferty CL, Engel BD, Schwede T, Durairaj J.   +7 more
europepmc   +1 more source

Robotic Control for Human–Robot Collaborative Assembly Based on Digital Human Model and Reinforcement Learning

Advanced Robotics Research, EarlyView.
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao, Hongzhou Ai, Wenjun Xu, Zude Zhou, Lihui Wang   +4 more
wiley   +1 more source

Enhancing medical Q&A systems with multimodal knowledge graphs and dual-layer attention mechanisms. [PDF]

PLoS One
Qiu G, Yuan Q, Wang Y, Qu P, Jia W.
europepmc   +1 more source

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source