A survey of multi-modal knowledge graphs: Technologies and trends
In recent years, Knowledge Graphs (KGs) have played a crucial role in the development of
advanced knowledge-intensive applications, such as recommender systems and semantic …
advanced knowledge-intensive applications, such as recommender systems and semantic …
Knowledge graphs meet multi-modal learning: A comprehensive survey
Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …
semantic web community's exploration into multi-modal dimensions unlocking new avenues …
Reasoning with language model prompting: A survey
Reasoning, as an essential ability for complex problem-solving, can provide back-end
support for various real-world applications, such as medical diagnosis, negotiation, etc. This …
support for various real-world applications, such as medical diagnosis, negotiation, etc. This …
A survey of knowledge graph reasoning on graph types: Static, dynamic, and multi-modal
Knowledge graph reasoning (KGR), aiming to deduce new facts from existing facts based on
mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research …
mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research …
Thought propagation: An analogical approach to complex reasoning with large language models
Large Language Models (LLMs) have achieved remarkable success in reasoning tasks with
the development of prompting methods. However, existing prompting approaches cannot …
the development of prompting methods. However, existing prompting approaches cannot …
Continual multimodal knowledge graph construction
Current Multimodal Knowledge Graph Construction (MKGC) models struggle with the real-
world dynamism of continuously emerging entities and relations, often succumbing to …
world dynamism of continuously emerging entities and relations, often succumbing to …
Analogykb: Unlocking analogical reasoning of language models with a million-scale knowledge base
Analogical reasoning is a fundamental cognitive ability of humans. However, current
language models (LMs) still struggle to achieve human-like performance in analogical …
language models (LMs) still struggle to achieve human-like performance in analogical …
A review of graph neural networks and pretrained language models for knowledge graph reasoning
J Ma, B Liu, K Li, C Li, F Zhang, X Luo, Y Qiao - Neurocomputing, 2024 - Elsevier
Abstract Knowledge Graph (KG) stores human knowledge facts in an intuitive graphical
structure but faces challenges such as incomplete construction or inability to handle new …
structure but faces challenges such as incomplete construction or inability to handle new …
Complex QA and language models hybrid architectures, Survey
This paper reviews the state-of-the-art of language models architectures and strategies for"
complex" question-answering (QA, CQA, CPS) with a focus on hybridization. Large …
complex" question-answering (QA, CQA, CPS) with a focus on hybridization. Large …
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
We introduce Buffer of Thoughts (BoT), a novel and versatile thought-augmented reasoning
approach for enhancing accuracy, efficiency and robustness of large language models …
approach for enhancing accuracy, efficiency and robustness of large language models …