Results 71 to 80 of about 185,676 (265)
CoRRReinforcement Learning from Human Feedback (RLHF) has greatly improved the performance of modern Large Language Models (LLMs). The RLHF process is resource-intensive and technically challenging, generally requiring a large collection of human preference labels over model-generated outputs.
Dakota Mahan +8 more
openaire +3 more sources
Organoids in pediatric cancer research
FEBS Letters, EarlyView.Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley +1 more source
Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system
FEBS Letters, EarlyView.Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley +1 more source
Personalized image generation with deep generative models: A decade survey
Computational Visual MediaRecent advances in generative models have significantly facilitated the development of personalized content creation. Given a small set of images containing a user-specific concept, personalized image generation allows the user to create images that ...
Yuxiang Wei +6 more
doaj +1 more source
Diversity and complexity in neural organoids
FEBS Letters, EarlyView.Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
wiley +1 more source
Optoelectronic generative adversarial networks
Communications PhysicsRecent breakthroughs in artificial intelligence generative content technology are driving transformational change. Diffractive optical networks offer a promising solution for high-speed, low-power generative models.
Jumin Qiu +5 more
doaj +1 more source
Generalizations of dual models
Nuclear Physics B, 1971 Generalizations of the dual model are discussed in the context of functional integral formulation of the theory. We notice that all the symmetries of dual amplitudes are led from the symmetries of the Lagrangian used for the measure of functional integration.
J.-L. GERVAIS, B. SAKITA
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FEBS Letters, EarlyView.Plasma membranes contain dynamic nanoscale domains that organize lipids and receptors. Because viruses operate at similar scales, this architecture shapes early infection steps, including attachment, receptor engagement, and entry. Using influenza A virus and HIV‐1 as examples, we highlight how receptor nanoclusters, multivalent glycan interactions ...
Jan Schlegel, Christian Sieben
wiley +1 more source
SystemsThe rapid development of generative AI technology has provided new pathways for iterative innovation in the business models of digital entrepreneurial enterprises.
Xuejiao Xu, Jing Zhang, Kun Zhang
doaj +1 more source
Proceedings of the AAAI Conference on Artificial Intelligence, 2018 We propose a novel approach for using unsupervised boosting to create an ensemble of generative models, where models are trained in sequence to correct earlier mistakes. Our meta-algorithmic framework can leverage any existing base learner that permits likelihood evaluation, including recent deep expressive models. Further, our approach
Aditya Grover, Stefano Ermon
openaire +4 more sources