为了应对这些挑战,我们提出了一个创新的端到端生成式框架用于多模态知识检索,简称为GeMKR。该框架利用大型语言模型(LLMs)作为其核心模型,基于LLMs即使在有限数据微调的情况下也能有效地充当虚拟知识库的前提。在GeMKR中,我们通过两步过程检索知识:1) 生成与查询相关的知识线索,2) 使用知识线索在数据库中搜索相关文档。
多模态机器学习,英文全称 MultiModal Machine Learning (MMML) 模态(modal)是事情经历和发生的方式,我们生活在一个由多种模态(Multimodal)信息构成的世界,包括视觉信息、听觉信息、文本信息、嗅觉信息等等,当研究的问题或者数据集包含多种这样的模态信息时我们称之为多模态问题,研究多模态问题是推动人工智能更好的了解和...
Multi-modal knowledge has been proven to provide critical cues for various computer vision tasks, such as image retrieval and vision question answering. In this paper, we integrate multi-modal knowledge into visual features to enhance the model's understanding of visual content and accomplish fine-...
Multi-modal retrieval is emerging as a new search paradigm that enables seamless information retrieval from various types of media. For example, users can simply snap a movie poster to search for relevant reviews and trailers. The mainstream solution to the problem is to learn a set of mapping...
In this paper, we describe a n ew paradigm for information retrieval in which the retrieval target is based on a model. Three types of models - linear, finite state, and knowledge models are discussed. These information retrieval scenarios often a rise from applications s uch a s environmental...
The constructed KB was evaluated how well it fits that knowledge domain regarding to its relevance for the application. The results show that the metadata in the presented KB could be exploited efficiently and, thus, it enhances the retrieval performance. 展开 ...
Tagging before Alignment: Integrating Multi-Modal Tags for Video-Text RetrievalChen Yizhen; Wang Jie; Lin Lijian; Qi Zhongang; Ma Jin; Shan Ying MRCN: A Novel Modality Restitution and Compensation Network for Visible-Infrared Person Re-Identificationyukang zhang; Yan Yan; Li Jie; Wang Hanzi...
So we propose a multi-modal retrieval model for mathematical expressions based on ConvNeXt and HFS to address the limitations of single-modal retrieval. For the image modal, mathematical expression retrieval is based on the similarity of image features and symbol-level features of the expression, ...
Knowledge-intensive tasks Measuring massive multitask language understanding, ICLR 2021 Paper Beyond the imitation game: Quantifying and extrapolating the capabilities of language models, Arxiv 2022 Paper Inverse scaling prize, 2022 Link Atlas: Few-shot Learning with Retrieval Augmented Language Models, Ar...
Inspired by synaesthesia, multi-modal cognitive computing endows machines with multi-sensory capabilities and has become the key to general artificial intelligence. With the explosion of multi-modal data such as image, video, text, and audio, a large number of methods have been developed to ...