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 …
Open-Ethical AI: Advancements in Open-Source Human-Centric Neural Language Models
This survey summarises the most recent methods for building and assessing helpful, honest,
and harmless neural language models, considering small, medium, and large-size models …
and harmless neural language models, considering small, medium, and large-size models …
Alleviating hallucinations of large language models through induced hallucinations
Despite their impressive capabilities, large language models (LLMs) have been observed to
generate responses that include inaccurate or fabricated information, a phenomenon …
generate responses that include inaccurate or fabricated information, a phenomenon …
Fake artificial intelligence generated contents (FAIGC): a survey of theories, detection methods, and opportunities
In recent years, generative artificial intelligence models, represented by Large Language
Models (LLMs) and Diffusion Models (DMs), have revolutionized content production …
Models (LLMs) and Diffusion Models (DMs), have revolutionized content production …
Decot: Debiasing chain-of-thought for knowledge-intensive tasks in large language models via causal intervention
Large language models (LLMs) often require task-relevant knowledge to augment their
internal knowledge through prompts. However, simply injecting external knowledge into …
internal knowledge through prompts. However, simply injecting external knowledge into …
A comprehensive survey of hallucination in large language, image, video and audio foundation models
The rapid advancement of foundation models (FMs) across language, image, audio, and
video domains has shown remarkable capabilities in diverse tasks. However, the …
video domains has shown remarkable capabilities in diverse tasks. However, the …
Literature Review of AI Hallucination Research Since the Advent of ChatGPT: Focusing on Papers from arXiv
DM Park, HJ Lee - Informatization Policy, 2024 - koreascience.kr
Hallucination is a significant barrier to the utilization of large-scale language models or
multimodal models. In this study, we collected 654 computer science papers with" …
multimodal models. In this study, we collected 654 computer science papers with" …
FedEAN: Entity-Aware Adversarial Negative Sampling for Federated Knowledge Graph Reasoning
Federated knowledge graph reasoning (FedKGR) aims to perform reasoning over different
clients while protecting data privacy, drawing increasing attention to its high practical value …
clients while protecting data privacy, drawing increasing attention to its high practical value …
A review on the reliability of knowledge graph: from a knowledge representation learning perspective
Y Yang, J Chen, Y Xiang - World Wide Web, 2025 - Springer
Abstract Knowledge graphs manage and organize data and information in a structured form,
which can provide effective support for various applications and services. Only reliable …
which can provide effective support for various applications and services. Only reliable …
HypoTermQA: Hypothetical Terms Dataset for Benchmarking Hallucination Tendency of LLMs
C Uluoglakci, TT Temizel - arXiv preprint arXiv:2402.16211, 2024 - arxiv.org
Hallucinations pose a significant challenge to the reliability and alignment of Large
Language Models (LLMs), limiting their widespread acceptance beyond chatbot …
Language Models (LLMs), limiting their widespread acceptance beyond chatbot …