Results 161 to 170 of about 4,199,951 (332)
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
Alisol F 24-acetate attenuated metabolic dysfunction-associated steatohepatitis by targeting the KEAP1/NRF2-mediated macrophage pyroptosis. [PDF]
Dong Z +7 more
europepmc +1 more source
Meir Michael Bar-Asher, Les Juifs dans le Coran, Préface de Mohammad Ali Amir-Moezzi. Albin Michel, 2019, 278 pages, 17 €. [PDF]
Jean-Marc Balhan
openalex +1 more source
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek +3 more
wiley +1 more source
Correction: Deep learning neural networks-based traffic predictors for V2X communication networks. [PDF]
Saady MM +6 more
europepmc +1 more source
Pak Biawak, a necrobot, embodies an unusual fusion of biology and robotics. Designed to repurpose natural structures after death, it challenges conventional boundaries between nature and engineering. Its movements are precise yet unsettling, raising questions about sustainability, ethics, and the untapped potential of biointegrated machines.
Leo Foulds +2 more
wiley +1 more source
Closure to “Evaluation of Explicit Numerical Solution Methods of the Muskingum Model” by Ali R. Vatankhah [PDF]
Ali R. Vatankhah
openalex +1 more source

