Results 181 to 190 of about 478,616 (367)
TASTE: Text-Aligned Speech Tokenization and Embedding for Spoken Language Modeling [PDF]
Large Language Models (LLMs) excel in text-based natural language processing tasks but remain constrained by their reliance on textual inputs and outputs. To enable more natural human-LLM interaction, recent progress have focused on deriving a spoken language model (SLM) that can not only listen but also generate speech.
arxiv
Evaluation of the effect of metal stents on dose perturbation in the carbon beam irradiation field
Abstract Propose Carbon ion therapy is indicated for cases in which stents have been inserted, such as bile ducts, but the effect of metal stents on carbon ion therapy is unclear. In this study, the dose perturbation of carbon ion therapy caused by metallic bile duct stents was evaluated by dosimetry. Materials and methods Five different types of metal
Yuya Miyasaka+8 more
wiley +1 more source
The mucosal pellicle (MP) is a biological film protecting the oral mucosa. It is composed of bounded salivary proteins and transmembrane mucin MUC1 expressed by oral epithelial cells.
Clément Nivet+16 more
doaj +1 more source
Thrombosis of Vertebral Artery Pressing on Glosso-Pharyngeal Nerve: Unilateral Loss of Taste at Back of Tongue [PDF]
F M Pope
openalex +1 more source
Closing the gap in plan quality: Leveraging deep‐learning dose prediction for adaptive radiotherapy
Abstract Purpose Balancing quality and efficiency has been a challenge for online adaptive therapy. Most systems start the online re‐optimization with the original planning goals. While some systems allow planners to modify the planning goals, achieving a high‐quality plan within time constraints remains a common barrier.
Sean J. Domal+9 more
wiley +1 more source
The effect of a high water intake on salt consumption, taste thresholds and salivary secretion in man [PDF]
H. E. de Wardener, Andrew Herxheimer
openalex +1 more source
Abstract Purpose Studies on deep learning dose prediction increasingly focus on 3D models with multiple input channels and data augmentation, which increases the training time and thus also the environmental burden and hampers the ease of re‐training. Here we compare 2D and 3D U‐Net models with clinical accepted plans to evaluate the appropriateness of
Rosalie Klarenberg+2 more
wiley +1 more source