1.2k citations · 1.2k across the 9 of their papers we have counts for
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Active Learning for Event Extraction with Memory-based Loss Prediction Model
Shirong Shen, Zhen Li, Guilin Qi
Event extraction (EE) plays an important role in many industrial application scenarios, and high-quality EE methods require a large amount of manual annotation data to train superv…
Multi-Compound Transformer for Accurate Biomedical Image Segmentation
Yuanfeng Ji, Ruimao Zhang, Huijie Wang +4
The recent vision transformer(i.e.for image classification) learns non-local attentive interaction of different patch tokens. However, prior arts miss learning the cross-scale depe…
CARLS: Cross-platform Asynchronous Representation Learning System
Chun-Ta Lu, Yun Zeng, Da-Cheng Juan +13
In this work, we propose CARLS, a novel framework for augmenting the capacity of existing deep learning frameworks by enabling multiple components -- model trainers, knowledge make…
Combining Supervised and Un-supervised Learning for Automatic Citrus Segmentation
Heqing Huang, Tongbin Huang, Zhen Li +2
Citrus segmentation is a key step of automatic citrus picking. While most current image segmentation approaches achieve good segmentation results by pixel-wise segmentation, these…
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
Chao Jia, Yinfei Yang, Ye Xia +7
Pre-trained representations are becoming crucial for many NLP and perception tasks. While representation learning in NLP has transitioned to training on raw text without human anno…