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Fine-tuning in the 2HDM

European Physical Journal C: Particles and Fields, 2022
The Two-Higgs Doublet Model (2HDM) is one of the most popular and natural extensions of the Higgs sector; but it has two potential fine-tuning problems, related to the electroweak (EW) breaking and the requirement of alignment with the SM Higgs boson. We
A. Bernal, J. A. Casas, J. M. Moreno
doaj   +3 more sources

Fine-tuning and structured prompting strategies for question answering over full-text biomedical research articles. [PDF]

PLoS ONE
ObjectivesThe ability of large language models (LLMs) to answer targeted scientific questions by synthesizing information from research articles remains an open research challenge.MethodsWe evaluated the effects of fine-tuning and a question-specific ...
Kaiming Tao, Rohit Satija, Jinru Zhou, Zachary A Osman, Vineet Ahluwalia, Chiara Sabatti, Robert W Shafer   +6 more
doaj   +2 more sources

Fine-tuning metabolic switches.

PLoS Biology, 2013
Cells get the energy for most of their activities in the form of adenosine triphosphate (ATP), which is generated through the breakdown of glucose and lipid molecules. Partial breakdown of a single glucose molecule through glycolysis yields 2 ATP molecules; and when glycolysis is followed by pyruvate decarboxylation and the tricarboxcylic acid (TCA ...
Caitlin Sedwick
doaj   +3 more sources

An efficient strategy for fine-tuning large language models [PDF]

Frontiers in Artificial Intelligence
IntroductionLarge Language Models (LLMs) achieve strong performance on many Natural Language Processing tasks, but adapting them to domain-specific applications is resource-intensive due to the cost of curating task-specific datasets and the compute ...
Benjamin Marsh, Adam Michaleas, Darrell O. Ricke, Shaun Monera, Shriya Zembruski   +4 more
doaj   +2 more sources

LLM Fine-Tuning: Concepts, Opportunities, and Challenges

Big Data and Cognitive Computing
As a foundation of large language models, fine-tuning drives rapid progress, broad applicability, and profound impacts on human–AI collaboration, surpassing earlier technological advancements.
Xiao-Kun Wu, Min Chen, Wanyi Li, Rui Wang, Limeng Lu, Jia Liu, Kai Hwang, Yixue Hao, Yanru Pan, Qingguo Meng, Kaibin Huang, Long Hu, Mohsen Guizani, Naipeng Chao, Giancarlo Fortino, Fei Lin, Yonglin Tian, Dusit Niyato, Fei-Yue Wang   +18 more
doaj   +2 more sources

Fine tuning, sequestering, and the swampland

Physics Letters B, 2019
We conjecture and present evidence that any effective field theory coupled to gravity in flat space admits at most a finite number of fine tunings, depending on the amount of supersymmetry and spacetime dimension. In particular, this means that there are
Jonathan J. Heckman, Cumrun Vafa
doaj   +3 more sources

Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

CoRR
In this paper, we introduce a novel learning paradigm for Adaptive Large Language Model (LLM) agents that eliminates the need for fine-tuning the underlying LLMs.
Huichi Zhou, Yihang Chen, Siyuan Guo, Xu Yan, Kin-Hei Lee, Zihan Wang, K. Lee, Guchun Zhang, Kun Shao, Linyi Yang, Jun Wang   +10 more
semanticscholar   +3 more sources

DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation [PDF]

Computer Vision and Pattern Recognition, 2022
Large text-to-image models achieved a remarkable leap in the evolution of AI, enabling high-quality and diverse synthesis of images from a given text prompt.
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Y. Pritch, Michael Rubinstein, Kfir Aberman   +5 more
semanticscholar   +1 more source

Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! [PDF]

International Conference on Learning Representations, 2023
Optimizing large language models (LLMs) for downstream use cases often involves the customization of pre-trained LLMs through further fine-tuning. Meta's open release of Llama models and OpenAI's APIs for fine-tuning GPT-3.5 Turbo on custom datasets also
Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson   +6 more
semanticscholar   +1 more source

Visual Instruction Tuning [PDF]

Neural Information Processing Systems, 2023
Instruction tuning large language models (LLMs) using machine-generated instruction-following data has improved zero-shot capabilities on new tasks, but the idea is less explored in the multimodal field. In this paper, we present the first attempt to use
Haotian Liu, Chunyuan Li, Qingyang Wu, Yong Jae Lee   +3 more
semanticscholar   +1 more source