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Contrast then Memorize: Semantic Neighbor Retrieval-Enhanced Inductive Multimodal Knowledge Graph Completion

Offered By: Association for Computing Machinery (ACM) via YouTube

Tags

Knowledge Graphs Courses Artificial Intelligence Courses Machine Learning Courses Reasoning Courses Information Retrieval Courses Contrastive Learning Courses

Course Description

Overview

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Explore a 15-minute conference talk presented at SIGIR 2024 focusing on innovative approaches to inductive multimodal knowledge graph completion. Delve into the "Contrast then Memorize" method, which enhances semantic neighbor retrieval for more effective graph completion. Learn how authors Yu Zhao, Ying Zhang, Baohang Zhou, Xinying Qian, Kehui Song, and Xiangrui Cai tackle the challenges of reasoning and knowledge graph expansion. Gain insights into cutting-edge techniques that combine contrastive learning and memorization strategies to improve the accuracy and efficiency of multimodal knowledge graph completion in inductive settings.

Syllabus

SIGIR 2024 M1.2 [fp] Contrast then Memorize: Semantic Neighbor Retrieval-Enhanced Inductive Multimod


Taught by

Association for Computing Machinery (ACM)

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