Contrastive Learning

Summary of Contrastive Learning Papers from ACL 2021

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Summary of Contrastive Learning Papers from ACL 2021

MLNLP(Machine Learning Algorithms and Natural Language Processing) community is one of the largest natural language processing communities both domestically and internationally, gathering over 500,000 subscribers, with an audience covering NLP master’s and PhD students, university teachers, and corporate researchers. The Vision of the Community is to promote communication and progress between academia, industry, and enthusiasts … Read more

Understanding Self-Supervised Learning

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Understanding Self-Supervised Learning

Self-Supervised Learning is a popular research area in recent years. It aims to extract the inherent representation features of unlabeled data by designing auxiliary tasks as supervisory signals, thereby enhancing the model’s feature extraction capabilities. Today, let’s explore what self-supervised learning is! 01 What is Self-Supervised Learning? Machine learning can be classified into supervised learning, … Read more

New SOTA in Text Representation: Prompt+ Contrastive Learning

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New SOTA in Text Representation: Prompt+ Contrastive Learning

MLNLP(Machine Learning Algorithms and Natural Language Processing) is one of the largest natural language processing communities in China and abroad, gathering over 500,000 subscribers, covering NLP master’s and PhD students, university professors, and corporate researchers. The vision of the community is to promote communication and progress between the academic and industrial circles of natural language … Read more

Prompt-Based Contrastive Learning for Sentence Representation

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Prompt-Based Contrastive Learning for Sentence Representation

MLNLP community is a well-known machine learning and natural language processing community in China and abroad, covering NLP graduate students, university teachers, and industry researchers. The community’s vision is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning, especially for beginners. Reprinted from | NewBeeNLP Author … Read more

Prompt Paradigms in Multimodal: CLIP

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Prompt Paradigms in Multimodal: CLIP

Machine Learning Algorithms and Natural Language Processing(ML-NLP) is one of the largest natural language processing communities both domestically and internationally, gathering over 500,000 subscribers, covering NLP master’s and doctoral students, university teachers, and corporate researchers. The Vision of the Communityis to promote communication and progress between the academic and industrial sectors of natural language processing … Read more

Prompt-Based Contrastive Learning for Sentence Representation

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Prompt-Based Contrastive Learning for Sentence Representation

This article is approximately 1100 words long and is recommended to be read in 5 minutes. This article proposes using prompts to capture sentence representations. Although language models like BERT have achieved significant results, they still perform poorly in terms of sentence embeddings due to issues of sentence bias and anisotropy; We found that using … Read more

Detection of False Data Injection Attacks Using Unsupervised and Supervised Learning

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Detection of False Data Injection Attacks Using Unsupervised and Supervised Learning

Reference Information (Click Title to Read Full Text) Huang Dongmei, Wang Yifan, Hu Anduo, et al. Detection method of false data injection attack based on unsupervised and supervised learning[J]. Electric Power Engineering Technology, 2024, 43(2):134-141. HUANG Dongmei, WANG Yifan, HU Anduo, et al. Detection method of false data injection attack based on unsupervised and supervised … Read more

How to Use Multi-Type Data to Pre-Train Multimodal Models?

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How to Use Multi-Type Data to Pre-Train Multimodal Models?

Click on the "Xiao Bai Learns Vision" above, select to add a "star" or "top". Important content delivered to you first. Guide to Extreme City This article reviews four papers on achieving multi-task unification in data or model structure, introducing the research direction of incorporating multiple types of data in the optimization of multimodal models. … Read more

FontDiffuser: One-Shot Font Generation with Denoising Diffusion

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FontDiffuser: One-Shot Font Generation with Denoising Diffusion

Follow our public account to discover the beauty of CV technology This article shares the AAAI 2024 paper FontDiffuser: One-Shot Font Generation via Denoising Diffusion with Multi-Scale Content Aggregation and Style Contrastive Learning, detailing the use of diffusion models for generating complex characters in any style. Detailed information is as follows: Authors: Yang Zhenhua, Peng … Read more