知识蒸馏(Knowledge Distillation)有效: 这里的蒸馏指将多个模型集成的结果蒸馏到单一模型中。这样蒸馏结果相比单一模型有更好的表现,可以认为蒸馏为该模型找到了更优的解。 自蒸馏(Self-Distillation) 有效: 即使把单一模型的结果进行蒸馏到另一个相同的模型,也会产生性能上的提升。 这里讨论的单一模型结构相同,仅有初...
Towards understanding ensemble, knowledge distillation, and self-distillation in deep learning 小张小张几点了 不要用温柔来对抗黑暗,要用火3 人赞同了该文章 目录 收起 Methodology and Intuition 神经网络集成 vs NTK特征图集成 深度学习中的集成:一个特征学习问题 多视图数据学习 导读: 深度学习中只是简单...
Towards understanding knowledge distillationKnowledge distillation, i.e. one classifier being trained on the outputs of another classifier, is an empirically very successful technique for knowledge transfer between classifiers. It has even been observed that classifiers learn much faster and more reliably ...
Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning Zeyuan Allen-Zhu, Yuanzhi Li, Zeyuan Allen-Zhu arXiv preprint|December 2020, (2012.09816) Publication Download BibTex We formally study how Ensemble of deep learning models can impr...
Changes in climate and energy technologies motivate a greater understanding of residential electricity usage and its relation to weather conditions. The re... CS Lee,Z Zhao,AS Stillwell - IOP Publishing Ltd 被引量: 0发表: 2024年 SUGAR: Pre-training 3D Visual Representations for Robotics Learning...
This duality is categorized into ’natural language understanding’ and ’natural language generation,’ forming the two pillars of NLP. However, both domains present formidable challenges. Even in the current theoretical and technological environment, creating a high-quality NLP system remains a ...
Kamath, A., Singh, M., LeCun, Y., Synnaeve, G., Misra, I., Carion, N.: Mdetr-modulated detection for end-to-end multi-modal understanding. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 1780–1790 (2021) ...
2024 CVPR RegionGPT RegionGPT: Towards region understanding vision language model GitHub 2024 arXiv TextHawk TextHawk: Exploring efficient fine-grained perception of multimodal large language models GitHub 2024 ACM TMM PEAR Multimodal PEAR: Chain-of-thought reasoning for multimodal sentiment analysis GitHu...
The Modality Focusing Hypothesis: Towards Understanding Crossmodal Knowledge Distillation. ICLR'23作者: Zihui Xue, Zhengqi Gao, Sucheng Ren, Hang Zhao [Knowledge Distillation] [Multi-Model Learn…
We introduce a Deep Contrastive Self-Supervised Learning (DCSSL) model that integrates a Natural Language Inference (NLI) dataset, a fine-tuned sentence encoder, and data augmentation to enhance the understanding of cyberbullying's nuanced semantics and offensiveness. The DCSSL model effectively ...