Results 121 to 130 of about 6,156,320 (380)
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Purpose/objectives Recent technological advancements have increased efficiency for clinical deliverability of online‐adaptive‐radiotherapy (oART). Previous cone‐beam‐computed‐tomography (CBCT) generations lacked the ability to provide reliable Hounsfield‐units (HU), thus requiring oART workflows to rely on synthetic‐CT (sCT) images derived ...
Jingwei Duan +7 more
wiley +1 more source
Prompt Optimization in Large Language Models
MathematicsPrompt optimization is a crucial task for improving the performance of large language models for downstream tasks. In this paper, a prompt is a sequence of n-grams selected from a vocabulary.
Antonio Sabbatella +4 more
doaj +1 more source
When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language Models [PDF]
arXiv, 2020 Transfer learning based on pretraining language models on a large amount of raw data has become a new norm to reach state-of-the-art performance in NLP. Still, it remains unclear how this approach should be applied for unseen languages that are not covered by any available large-scale multilingual language model and for which only a small amount of raw
arxiv
Can Large Language Models design a Robot? [PDF]
arXiv, 2023 Large Language Models can lead researchers in the design of robots.
arxiv
Closing the gap in plan quality: Leveraging deep‐learning dose prediction for adaptive radiotherapy
Journal of Applied Clinical Medical Physics, EarlyView.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
Large language models (ChatGPT) in medical education: Embrace or abjure?
The Asia Pacific Scholar, 2023 Nathasha Luke +4 more
doaj +1 more source
Improving Language Modelling with Noise-contrastive estimation
, 2017 Neural language models do not scale well when the vocabulary is large. Noise-contrastive estimation (NCE) is a sampling-based method that allows for fast learning with large vocabularies.
Grzes, Marek, Liza, Farhana Ferdousi
core +1 more source
Dose rate correction of a diode array for universal wedge field dosimetric verification
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Purpose To study the performance of MapCHECK 3 (MC3) in measuring universal wedge fields and propose a dose rate correction strategy to improve MC3 measurement accuracy. Materials and methods Universal wedge fields with different wedge angles and field sizes were measured at different depths using MC3.
Linyi Shen +6 more
wiley +1 more source
Large scale paired antibody language models.
PLoS Computational BiologyAntibodies are proteins produced by the immune system that can identify and neutralise a wide variety of antigens with high specificity and affinity, and constitute the most successful class of biotherapeutics.
Henry Kenlay +5 more
doaj +1 more source
Alternating Recurrent Dialog Model with Large-scale Pre-trained Language Models [PDF]
, 2021 Qingyang Wu, Yichi Zhang, Yu Li, Zhou Yu
openalex +1 more source