论文题目:Unifying Large Language Models and Knowledge Graphs: A Roadmap 作者:Shirui Pan; Linhao Luo; Yufei Wang; Chen Chen; Jiapu Wang; Xindong Wu 单位:Griffith University, Monash University, Nan…
论文题目:Unifying Large Language Models and Knowledge Graphs: A Roadmap(统一大型语言模型和知识图:路线图) 作者&团队:Shirui Pan, Senior Member, IEEE, Linhao Luo,Yufei Wang, Chen Chen, Jiapu Wang, Xindong Wu, Fellow, IEEE 研究动机: ①LLMs的局限性:LLMs是黑盒模型,通常难以捕捉和获取事实知识。
Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the field of natural language processing and artificial intelligence, due to their emergent ability and generalizability. However, LLMs are black-box models, which often fall short of capturing and accessing ...
Just a few years ago, intelligent machines that understand and respond to you were a thing of Sci-Fi — something you could only find in Star Trek. Today, large language models (LLMs) like ChatGPT are at our fingertips, waiting for our prompts. The future is now. Knowledge graphs are ...
A collection of papers and resources about unifying large language models (LLMs) and knowledge graphs (KGs). Large language models (LLMs) have achieved remarkable success and generalizability in various applications. However, they often fall short of capturing and accessing factual knowledge. Knowledge...
The recent advent of Large Language Models (LLMs) has ushered sophisticated reasoning capabilities into the realm of video through Video Large Language Models (VideoLLMs). However, VideoLLMs currently rely on a single vision encoder for all of their visual processing, which limits the amount and...
Large language models (LLMs) have recently been extended to the vision-language realm, obtaining impressive general multi-modal capabilities. However, the exploration of multi-modal large language models (MLLMs) for remote sensing (RS) data is still in its infancy, lacking datasets and with unsat...
Technology practitioners have said that a new opportunity has emerged to explore multimodality through a unified architecture, eliminating the need to combine complex diffusion models with large language models (LLMs). "In the future, the multimodal world model will promote scenario applications such as...
我们可以天真地将 CLIP 中的视觉和文本编码器(Radford et al., 2021)应用到我们的任务中;然而,在我们的实验中,我们观察到 Vision Encoder 无法用更细粒度的信息对屏幕截图进行编码;因此,我们建议使用 Large Vision Language Models 作为 Document Screenshot 编码器。