Results 81 to 90 of about 51,918 (265)

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

open access: yesAdvanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung   +9 more
wiley   +1 more source

Transducers Across Scales and Frequencies: A System‐Level Framework for Multiphysics Integration and Co‐Design

open access: yesAdvanced Materials Technologies, EarlyView.
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu   +8 more
wiley   +1 more source

Evaluating semantic relations in neural word embeddings with biomedical and general domain knowledge bases

open access: yesBMC Medical Informatics and Decision Making, 2018
Background In the past few years, neural word embeddings have been widely used in text mining. However, the vector representations of word embeddings mostly act as a black box in downstream applications using them, thereby limiting their interpretability.
Zhiwei Chen   +3 more
doaj   +1 more source

Scalable Task Planning via Large Language Models and Structured World Representations

open access: yesAdvanced Robotics Research, EarlyView.
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari   +4 more
wiley   +1 more source

Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space

open access: yesAdvanced Robotics Research, EarlyView.
A quadruped robot masters dynamic jumps through constrained spaces with animal‐inspired moves and intelligent vision control. This hierarchical learning approach combines imitation of biological agility with real‐time trajectory planning. Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating ...
Zeren Luo   +6 more
wiley   +1 more source

Graph reasoning over explicit semantic relation

open access: yesHigh-Confidence Computing
Multi-hop reasoning over language or graphs represents a significant challenge in contemporary research, particularly with the reliance on deep neural networks.
Tianyou Zhu   +5 more
doaj   +1 more source

Relating Goal and Commitment Semantics [PDF]

open access: yes, 2012
Whereas commitments capture how an agent relates with another agent, (private) goals describe states of the world that an agent is motivated to bring about. Researchers have observed that goals and commitments are complementary, but have not yet developed a combined operational semantics for them.
Pankaj R. Telang   +2 more
openaire   +1 more source

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

open access: yesAdvanced 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

Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback

open access: yesAdvanced Robotics Research, EarlyView.
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

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