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05/24/2023
Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts
The explosive growth of language models and their applications have led ...
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05/15/2023
Symbol tuning improves in-context learning in language models
We present symbol tuning - finetuning language models on in-context inpu...
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01/31/2023
The Flan Collection: Designing Data and Methods for Effective Instruction Tuning
We study the design decisions of publicly available instruction tuning m...
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10/21/2022
Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation
Knowledge distillation is one of the primary methods of transferring kno...
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10/20/2022
Large Language Models Can Self-Improve
Large Language Models (LLMs) have achieved excellent performances in var...
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05/21/2022
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
We propose a novel prompting strategy, least-to-most prompting, that ena...
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03/24/2022
Token Dropping for Efficient BERT Pretraining
Transformer-based models generally allocate the same amount of computati...
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10/08/2021
Speeding up Deep Model Training by Sharing Weights and Then Unsharing
We propose a simple and efficient approach for training the BERT model. ...
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03/05/2020
Talking-Heads Attention
We introduce "talking-heads attention" - a variation on multi-head atten...
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02/18/2020
Dataset of Segmented Nuclei in Hematoxylin and Eosin Stained Histopathology Images of 10 Cancer Types
The distribution and appearance of nuclei are essential markers for the ...
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09/26/2019
Exascale Deep Learning to Accelerate Cancer Research
Deep learning, through the use of neural networks, has demonstrated rema...
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09/06/2019
High Resolution Medical Image Analysis with Spatial Partitioning
Medical images such as 3D computerized tomography (CT) scans and patholo...
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07/09/2019
Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types
Deep learning classifiers for characterization of whole slide tissue mor...
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05/26/2019
Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor Infiltrating Lymphocytes in Invasive Breast Cancer
Quantitative assessment of Tumor-TIL spatial relationships is increasing...
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04/09/2019
Label Super Resolution with Inter-Instance Loss
For the task of semantic segmentation, high-resolution (pixel-level) gro...
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12/13/2017
Unsupervised Histopathology Image Synthesis
Hematoxylin and Eosin stained histopathology image analysis is essential...
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04/03/2017
Sparse Autoencoder for Unsupervised Nucleus Detection and Representation in Histopathology Images
Histopathology images are crucial to the study of complex diseases such ...
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12/20/2016
Center-Focusing Multi-task CNN with Injected Features for Classification of Glioma Nuclear Images
Classifying the various shapes and attributes of a glioma cell nucleus i...
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11/17/2016
Squared Earth Mover's Distance-based Loss for Training Deep Neural Networks
In the context of single-label classification, despite the huge success ...
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08/23/2016
Neural Networks with Smooth Adaptive Activation Functions for Regression
In Neural Networks (NN), Adaptive Activation Functions (AAF) have parame...
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04/29/2015
