The paper discusses TWIG (Topologically-Weighted Intelligence Generation), an innovative paradigm for simulating the output of Knowledge Graph Embeddings (KGEs) using a significantly lesser number of parameters. TWIG learns from inputs…
Continue readingThe article discusses the challenges in Knowledge Graph (KG) learning due to its immense size. Four key deficiencies are identified: lack of expert knowledge integration, instability to node degree extremity…
Continue readingThis academic article presents CADReN, a new method for estimating node importance in Knowledge Graphs (KGs), crucial for integrating external information into Large Language Models. Traditional methods lack adaptability to…
Continue readingThis academic article is a thorough review of over 300 articles that focus on the use of Knowledge Graphs (KGs) in Multi-modal Learning. It discusses two main aspects: KG-driven Multi-Modal…
Continue readingThe paper discusses the development and application of Kyurem, an interactive widget library designed to aid in human-centered knowledge acquisition and integration tasks within knowledge graphs (KGs). The tool provides…
Continue readingThe article discusses the limitations of Large Language Models (LLMs) and Vision Models (LVMs) in capturing holistic meaning in multimodal online marketing campaigns. The authors propose a framework that combines…
Continue readingThe paper discusses the importance of augmenting large language models (LLMs) with user-specific knowledge for real-world applications like personal AI assistants. The authors focus on prompt-to-triple (P2T) generation, exploring methods…
Continue readingThe article discusses the development of an interactive and intelligent tool for Root Cause Analysis (RCA) in the manufacturing of electric vehicles. Traditionally, RCA is conducted manually, which can be…
Continue readingThe paper discusses the limitations of the standard evaluation protocol for Knowledge Graph Completion methods, which involves ranking every entity of a Knowledge Graph. The authors argue that this task…
Continue readingThe paper explores how to enhance biomedical language models using adapter modules and knowledge graphs. The approach involves partitioning knowledge graphs into smaller subgraphs, fine-tuning adapter modules for each subgraph,…
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