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New TOFU model enhances multi-modal knowledge graph reasoning

By PulseAugur Editorial · [1 sources] ·

Researchers have developed TOFU, a novel token-based foundation model designed for multi-modal knowledge graph reasoning (MMKGR). This model discretizes structural, visual, and textual data into modality-specific tokens, enabling it to generalize effectively across different knowledge graphs. TOFU utilizes a hierarchical fusion architecture with message-mixing mechanisms to process these tokens and extract transferable features. Experiments across 17 diverse MMKGs demonstrate that TOFU surpasses existing knowledge graph foundation models and MMKGR baselines, particularly on unseen knowledge graphs. AI

IMPACT This research could improve the ability of AI systems to reason across diverse and complex knowledge graphs by better integrating multi-modal data.

RANK_REASON The cluster contains an academic paper detailing a new model and its experimental results. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New TOFU model enhances multi-modal knowledge graph reasoning

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The cluster contains an academic paper detailing a new model and its experimental results. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Yichi Zhang, Zhuo Chen, Lingbing Guo, Wen Zhang, Huajun Chen ·

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

    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…

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