Multimodal Prompt Tuning: How Effective Are You?

Multimodal Prompt Tuning: How Effective Are You?

MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP master’s and doctoral students, university teachers, and researchers from enterprises. The community’s vision is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning at home and abroad, especially … Read more

Overview of Multimodal Sentiment Analysis

Overview of Multimodal Sentiment Analysis

Follow the official account “ML_NLP“ Set as “Starred“, delivering heavy content promptly! Introduction With the rapid development of social networks, the ways people express themselves on platforms have become increasingly rich, such as expressing emotions and opinions through images, text, and videos. Analyzing the emotions in multimodal data (this article refers to sound, images, and … Read more

How AI Multimodal Platform Design Supports Low-Cost Business Development

How AI Multimodal Platform Design Supports Low-Cost Business Development

This article is authorized to be reproduced from: 58UXD(ID:i58UXD) The design of AI multimodal platforms is a challenging yet opportunity-filled field. Our multimodal AI platform is a comprehensive platform that integrates multimodal AI technologies such as image generation, video generation, and content understanding. The platform deploys industry-leading open-source and commercial model capabilities in real-time, while … Read more

Summary of NLP and CV Fusion in Multimodal Systems

Summary of NLP and CV Fusion in Multimodal Systems

Follow the WeChat public account “ML_NLP“ Set it as “Starred“, delivering heavy content at the first time! Reprinted from | NLP from Beginner to Abandon Written by | Sanhe Factory Girl Edited by | zenRRan The first exposure to multimodal was a Douyin recommendation project, which involved some videos, titles, user likes, collections, etc., to … Read more

Research Progress on Multimodal Named Entity Recognition Methods

Research Progress on Multimodal Named Entity Recognition Methods

Research Progress on Multimodal Named Entity Recognition Methods Wang Hairong1,2, Xu Xi1, Wang Tong1, Jing Boxiang1 1. School of Computer Science and Engineering, Northern Minzu University; 2. Key Laboratory of Intelligent Processing of Image and Graphics, Northern Minzu University Click “Read the Original” at the end of the article to view the literature! Table of … Read more

Chen Li: The Significance of Multimodal Discourse in English Courses

Chen Li: The Significance of Multimodal Discourse in English Courses

1 What Is Multimodal Discourse 1.1 What is discourse? Discourse is an important means for humans to convey information, and it is a linguistic unit with communicative significance or contextual semantics. 1.2 The forms of discourse can be monomodal or multimodal. Here, mode refers to the pattern or method of information transmission in discourse. 1.3 … Read more

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

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

The Significance of Multimodal Discourse in English Courses

The Significance of Multimodal Discourse in English Courses

1 What Is Multimodal Discourse 1.1 What is Discourse? Discourse is an important means for humans to convey information, and it is a linguistic unit with communicative significance or contextual semantics. 1.2 The forms of discourse can be monomodal (单模态) or multimodal (多模态). Here, mode refers to the patterns or methods of conveying information in … Read more

Multimodal Biomedical AI in the Era of Large Models

Multimodal Biomedical AI in the Era of Large Models

Most applications of artificial intelligence in medicine utilize a single data modality to address tasks within a narrow scope, such as computed tomography (CT) scans or retinal photographs. However, clinicians integrate multi-source, multimodal data for diagnosis, prognosis assessment, and treatment planning. In this review, the authors explore the applications of multimodal datasets in healthcare, the … Read more

Lightweight Adaptation Techniques for Multimodal Pre-trained Models

Lightweight Adaptation Techniques for Multimodal Pre-trained Models

This article is approximately 4200 words long, and it is recommended to read it in 8 minutes This article introduces the exploration and sharing of lightweight adaptation techniques for multimodal pre-trained models. Pre-trained language models such as BERT and GPT-3 have been proven to achieve excellent results in the NLP field. With the gradual maturity … Read more