Multi-Modal

Fudan University: Latest Survey on Multi-Modal Knowledge Graphs

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Fudan University: Latest Survey on Multi-Modal Knowledge Graphs

This article is approximately 2500 words long and is recommended for a 5-minute read. This article summarizes a knowledge-based direction paper, integrating multi-modal knowledge into multi-modal knowledge graphs. This blog post summarizes a knowledge-based direction paper, integrating multi-modal knowledge into multi-modal knowledge graphs. From Fudan University, here’s the path: Title: Multi-Modal Knowledge Graph Construction and … Read more

A Study on the Application of Multi-modal Teaching Mode in Junior High School English Grammar Teaching

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A Study on the Application of Multi-modal Teaching Mode in Junior High School English Grammar Teaching

Abstract: This paper is based on the concept and characteristics of multi-modal teaching mode, taking a grammar review class as an example. It explores the practical path of integrating multi-modal teaching mode in grammar teaching through five levels: communicative introduction, grammar presentation, expanded practice, cultural connection, and transfer output. It elaborates on the CPPCO multi-modal … Read more

An Overview of Multi-Modal Summarization

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An Overview of Multi-Modal Summarization

MLNLP ( Machine Learning Algorithms and Natural Language Processing ) community is a well-known natural language processing community both domestically and internationally, covering NLP master’s and Ph.D. students, university professors, and researchers in enterprises. The vision of the community is to promote communication between the academic and industrial communities of natural language processing and machine … Read more

ACL 2024: Cambridge Team Open Sources Pre-trained Multi-modal Retriever

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ACL 2024: Cambridge Team Open Sources Pre-trained Multi-modal Retriever

Follow our public account to discover the beauty of CV technology This article shares the ACL 2024 paper PreFLMR: Scaling Up Fine-Grained Late-Interaction Multi-modal Retrievers, open-sourced by the Cambridge University team, empowering multi-modal large model RAG applications, and is the first pre-trained general multi-modal late-interaction knowledge retriever. Paper link: https://arxiv.org/abs/2402.08327 Project homepage: https://preflmr.github.io/ Introduction The … Read more

Transformer Advances Towards Dynamic Routing: TRAR for VQA and REC SOTA

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Transformer Advances Towards Dynamic Routing: TRAR for VQA and REC SOTA

Follow our public account to discover the beauty of CV technology 1 Introduction Due to its superior capability for modeling global dependencies, the Transformer and its variants have become the primary architecture for many visual and language tasks. However, tasks like Visual Question Answering (VQA) and Referencing Expression Comprehension (REC) often require multi-modal predictions that … Read more

Embodied Intelligence and Multi-modal Language Models: Is GPT-4 Vision the Strongest Agent?

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Embodied Intelligence and Multi-modal Language Models: Is GPT-4 Vision the Strongest Agent?

Author: PCA-EVAL Team Affiliation: Peking University & Tencent Abstract: Researchers from Peking University and Tencent have proposed the PCA-EVAL multi-modal embodied decision-making intelligence evaluation set. By comparing end-to-end decision-making methods based on multi-modal models with tool invocation methods based on LLMs, it has been observed that GPT-4 Vision demonstrates outstanding end-to-end decision-making capabilities from multi-modal … Read more

Overview of 26 SOTA Multi-Modal Large Language Models

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Overview of 26 SOTA Multi-Modal Large Language Models

Machine Heart Report Machine Heart Editorial Team What is the progress of multi-modal large language models?Here are 26 of the current best multi-modal large language models. The focus in the field of AI is shifting from large language models (LLMs) to multi-modal capabilities. Thus, multi-modal large language models (MM-LLMs) that enable LLMs to have multi-modal … Read more

What Cross-Modal Scenarios Does GraphRAG Support?

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What Cross-Modal Scenarios Does GraphRAG Support?

What Cross-Modal Scenarios Does GraphRAG Support? No Small Talk, Straight to the Point GraphRAG (Graph-based Retrieval-Augmented Generation) is a framework that combines knowledge graphs and retrieval-augmented generation technology, effectively handling cross-modal scenarios and supporting various complex data types and application scenarios. Below, we will introduce the main cross-modal scenarios supported by GraphRAG. 1. Text-Image Question … Read more

Phidata: A Framework for Multi-Modal Agents

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Phidata: A Framework for Multi-Modal Agents

More AI Open Source Tools: https://www.aiinn.cn/ Phidata is a framework for building multi-modal agents. Using Phidata, you can: build multi-modal agents with memory, knowledge, tools, and reasoning. Establish a team of agents that can collaborate to solve problems. Chat with your agents using a beautiful Agent UI. 16200 Stars 2200 Forks 28 Issues 82 Contributors … Read more