English(EN) Every Little Helps: Building Knowledge Graph Foundation Model with Fine-grained Transferable Multi-modal Tokens

新型TOFU模型增强多模态知识图谱推理能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-28 04:00

研究人员开发了TOFU，一种新颖的、基于令牌的基础模型，专为多模态知识图谱推理（MMKGR）设计。该模型将结构化、视觉和文本数据离散化为特定模态的令牌，使其能够有效地泛化到不同的知识图谱。TOFU采用分层融合架构和消息混合机制来处理这些令牌并提取可迁移特征。在17个不同的MMKG上的实验表明，TOFU在现有知识图谱基础模型和MMKGR基线之上，尤其是在未见过的知识图谱上表现更优。 AI

影响这项研究通过更好地整合多模态数据，有望提高人工智能系统在不同复杂知识图谱之间进行推理的能力。

排序理由该集群包含一篇详细介绍新模型及其实验结果的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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报道来源 [1]

arXiv cs.CL TIER_1 English(EN) · Yichi Zhang, Zhuo Chen, Lingbing Guo, Wen Zhang, Huajun Chen · 2026-10-28 04:00

点滴皆有助益：利用细粒度可迁移多模态令牌构建知识图谱基础模型

arXiv:2602.15896v2 Announce Type: replace Abstract: Multi-modal knowledge graph reasoning (MMKGR) aims to predict the missing links by exploiting both graph structure information and multi-modal entity contents. Most existing works are designed for a transductive setting, which l…

本文如何被排名

报道来源 [1]

点滴皆有助益：利用细粒度可迁移多模态令牌构建知识图谱基础模型

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