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The emerging trend of advancing generalist artificial intelligence, such as GPTv4 and Gemini, has reshaped the landscape of research (academia and industry) in machine learning and many other research areas.
The proposed uscf rating system, its development, theory, and applications
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Improving language understanding by generative pre-training
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A baseline for few-shot image classification
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Applying deep matching networks to chinese medical question answering: A study and a dataset
J. He, M. Fu, and M. Tu · 2019
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Language models are few-shot learners
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Sensecare: A research platform for medical image informatics and interactive 3d visualization
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Scaling laws for neural language models
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Few-shot medical image segmentation using a global correlation network with discriminative embedding
L. Sun, C. Li, X. Ding, Y. Huang, G. Wang, and Y. Yu · 2020
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Rethinking few-shot image classification: a good embedding is all you need?
Y. Tian, Y. Wang, D. Krishnan, J. B. Tenenbaum, and P. Isola · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, et al · 2021
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Learning transferable visual models from natural language supervision
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Training a helpful and harmless assistant with reinforcement learning from human feedback
Y. Bai, A. Jones, K. Ndousse, A. Askell, A. Chen, N. DasSarma, D. Drain, S. Fort, D. Ganguli, T. Henighan, et al · 2022
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Gptq: Accurate post-training quantization for generative pre-trained transformers
E. Frantar, S. Ashkboos, T. Hoefler, and D. Alistarh · 2022
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Medical image understanding with pretrained vision language models: A comprehensive study
Z. Qin, H. Yi, Q. Lao, and K. Li · 2022
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Fhist: A benchmark for few-shot classification of histological images
F. Shakeri, M. Boudiaf, S. Mohammadi, I. Sheth, M. Havaei, I. B. Ayed, and S. E. Kahou · 2022
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Y. Chen, Z. Wang, X. Xing, Z. Xu, K. Fang, J. Wang, S. Li, J. Wu, Q. Liu, X. Xu, et al · 2023
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
W.-L. Chiang, Z. Li, Z. Lin, Y. Sheng, Z. Wu, H. Zhang, L. Zheng, S. Zhuang, Y. Zhuang, J. E. Gonzalez, et al · 2023
Awq: Activation-aware weight quantization for llm compression and acceleration
J. Lin, J. Tang, H. Tang, S. Yang, X. Dang, and S. Han · 2023
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X. Luo, J. Fu, Y. Zhong, S. Liu, B. Han, M. Astaraki, S. Bendazzoli, I. Toma-Dasu, Y. Ye, Z. Chen, et al · 2023
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Foundation models for generalist medical artificial intelligence
M. Moor, O. Banerjee, Z. S. H. Abad, H. M. Krumholz, J. Leskovec, E. J. Topol, and P. Rajpurkar · 2023
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P. Tan, M. Li, L. Zhang, Z. Hu, and L. Hong · 2023
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Sa-med2d-20m dataset: Segment anything in 2d medical imaging with 20 million masks
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Cited alongside, same era.
Flashattention-2: Faster attention with better parallelism and work partitioning
T. Dao · 2023
Cited alongside, same era.
Qlora: Efficient finetuning of quantized llms
T. Dettmers, A. Pagnoni, A. Holtzman, and L. Zettlemoyer · 2023
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A large-scale synthetic pathological dataset for deep learning-enabled segmentation of breast cancer
K. Ding, M. Zhou, H. Wang, O. Gevaert, D. Metaxas, and S. Zhang · 2023
Cited alongside, same era.
The calla dataset: Probing llms’ interactive knowledge acquisition from chinese medical literature
Y. Du, S. Zhao, Y. Chen, R. Bai, J. Liu, H. Wu, H. Wang, and B. Qin · 2023
Cited alongside, same era.
Pathoduet: Foundation models for pathological slide analysis of h&e and ihc stains
S. Hua, F. Yan, T. Shen, and X. Zhang · 2023
Cited alongside, same era.
Deblurring masked autoencoder is better recipe for ultrasound image recognition
Q. Kang, J. Gao, K. Li, and Q. Lao · 2023
Cited alongside, same era.
A. Kirillov, E. Mintun, N. Ravi, H. Mao, C. Rolland, L. Gustafson, T. Xiao, S. Whitehead, A. C. Berg, W.-Y. Lo, P. Dollár, and R. Girshick · 2023
Cited alongside, same era.
J. Ye, J. Cheng, J. Chen, Z. Deng, T. Li, H. Wang, Y. Su, Z. Huang, J. Chen, L. Jiang, et al · 2023
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Text-guided foundation model adaptation for pathological image classification
Y. Zhang, J. Gao, M. Zhou, X. Wang, Y. Qiao, S. Zhang, and D. Wang · 2023
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A foundation model for generalizable disease detection from retinal images
Y. Zhou, M. A. Chia, S. K. Wagner, M. S. Ayhan, D. J. Williamson, R. R. Struyven, T. Liu, M. Xu, M. G. Lozano, P. Woodward-Court, et al · 2023
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Segment anything model for medical images?
Y. Huang, X. Yang, L. Liu, H. Zhou, A. Chang, X. Zhou, R. Chen, J. Yu, J. Chen, C. Chen, et al · 2024
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J. Jiao, J. Zhou, X. Li, M. Xia, Y. Huang, L. Huang, N. Wang, X. Zhang, S. Zhou, Y. Wang, and Y. Guo · 2024
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Segment anything in medical images
J. Ma, Y. He, F. Li, L. Han, C. You, and B. Wang · 2024
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On the challenges and perspectives of foundation models for medical image analysis
S. Zhang and D. Metaxas · 2024
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Data-centric foundation models in computational healthcare: A survey
Y. Zhang, J. Gao, Z. Tan, L. Zhou, K. Ding, M. Zhou, S. Zhang, and D. Wang · 2024
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