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09/13/2023
Scaled Prompt-Tuning for Few-Shot Natural Language Generation
The increasingly Large Language Models (LLMs) demonstrate stronger langu...
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06/06/2023
Supervised Knowledge May Hurt Novel Class Discovery Performance
Novel class discovery (NCD) aims to infer novel categories in an unlabel...
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05/03/2023
DocLangID: Improving Few-Shot Training to Identify the Language of Historical Documents
Language identification describes the task of recognizing the language o...
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11/23/2022
Join the High Accuracy Club on ImageNet with A Binary Neural Network Ticket
Binary neural networks are the extreme case of network quantization, whi...
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10/29/2022
Empirical Evaluation of Post-Training Quantization Methods for Language Tasks
Transformer-based architectures like BERT have achieved great success in...
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09/19/2022
A Closer Look at Novel Class Discovery from the Labeled Set
Novel class discovery (NCD) aims to infer novel categories in an unlabel...
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07/14/2021
Synthesis in Style: Semantic Segmentation of Historical Documents using Synthetic Data
One of the most pressing problems in the automated analysis of historica...
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06/13/2021
BoolNet: Minimizing The Energy Consumption of Binary Neural Networks
Recent works on Binary Neural Networks (BNNs) have made promising progre...
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06/02/2021
Not All Knowledge Is Created Equal
Mutual knowledge distillation (MKD) improves a model by distilling knowl...
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04/15/2021
AsymmNet: Towards ultralight convolution neural networks using asymmetrical bottlenecks
Deep convolutional neural networks (CNN) have achieved astonishing resul...
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03/22/2021
Evaluating Post-Training Compression in GANs using Locality-Sensitive Hashing
The analysis of the compression effects in generative adversarial networ...
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10/21/2020
One Model to Reconstruct Them All: A Novel Way to Use the Stochastic Noise in StyleGAN
Generative Adversarial Networks (GANs) have achieved state-of-the-art pe...
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01/16/2020
MeliusNet: Can Binary Neural Networks Achieve MobileNet-level Accuracy?
Binary Neural Networks (BNNs) are neural networks which use binary weigh...
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01/10/2020
microbatchGAN: Stimulating Diversity with Multi-Adversarial Discrimination
We propose to tackle the mode collapse problem in generative adversarial...
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11/19/2019
KISS: Keeping It Simple for Scene Text Recognition
Over the past few years, several new methods for scene text recognition ...
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06/19/2019
Back to Simplicity: How to Train Accurate BNNs from Scratch?
Binary Neural Networks (BNNs) show promising progress in reducing comput...
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12/05/2018
Training Competitive Binary Neural Networks from Scratch
Convolutional neural networks have achieved astonishing results in diffe...
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11/22/2018
Multi-Task Generative Adversarial Network for Handling Imbalanced Clinical Data
We propose a new generative adversarial architecture to mitigate imbalan...
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11/14/2018
LoANs: Weakly Supervised Object Detection with Localizer Assessor Networks
Recently, deep neural networks have achieved remarkable performance on t...
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11/05/2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Gliomas are the most common primary brain malignancies, with different d...
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10/09/2018
Conditional Generative Refinement Adversarial Networks for Unbalanced Medical Image Semantic Segmentation
We propose a new generative adversarial architecture to mitigate imbalan...
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09/27/2018
Learning to Train a Binary Neural Network
Convolutional neural networks have achieved astonishing results in diffe...
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07/30/2018
Dropout-GAN: Learning from a Dynamic Ensemble of Discriminators
We propose to incorporate adversarial dropout in generative multi-advers...
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12/14/2017
SEE: Towards Semi-Supervised End-to-End Scene Text Recognition
Detecting and recognizing text in natural scene images is a challenging,...
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07/27/2017
STN-OCR: A single Neural Network for Text Detection and Text Recognition
Detecting and recognizing text in natural scene images is a challenging,...
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05/27/2017
BMXNet: An Open-Source Binary Neural Network Implementation Based on MXNet
Binary Neural Networks (BNNs) can drastically reduce memory size and acc...
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04/04/2016
