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Unifying large language models and knowledge graphs: A roadmap
Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …
field of natural language processing and artificial intelligence, due to their emergent ability …
Are Large Language Models a Good Replacement of Taxonomies?
Large language models (LLMs) demonstrate an impressive ability to internalize knowledge
and answer natural language questions. Although previous studies validate that LLMs …
and answer natural language questions. Although previous studies validate that LLMs …
Direct evaluation of chain-of-thought in multi-hop reasoning with knowledge graphs
Large language models (LLMs) demonstrate strong reasoning abilities when prompted to
generate chain-of-thought (CoT) explanations alongside answers. However, previous …
generate chain-of-thought (CoT) explanations alongside answers. However, previous …
[HTML][HTML] Assessing how accurately large language models encode and apply the common European framework of reference for languages
L Benedetto, G Gaudeau, A Caines, P Buttery - Computers and Education …, 2025 - Elsevier
Abstract Large Language Models (LLMs) can have a transformative effect on a variety of
domains, including education, and it is therefore pressing to understand whether these …
domains, including education, and it is therefore pressing to understand whether these …
[HTML][HTML] Large Language Models, scientific knowledge and factuality: A framework to streamline human expert evaluation
Objective: The paper introduces a framework for the evaluation of the encoding of factual
scientific knowledge, designed to streamline the manual evaluation process typically …
scientific knowledge, designed to streamline the manual evaluation process typically …
KGPA: Robustness Evaluation for Large Language Models via Cross-Domain Knowledge Graphs
Existing frameworks for assessing robustness of large language models (LLMs) overly
depend on specific benchmarks, increasing costs and failing to evaluate performance of …
depend on specific benchmarks, increasing costs and failing to evaluate performance of …
Factual confidence of LLMs: On reliability and robustness of current estimators
M Mahaut, L Aina, P Czarnowska, M Hardalov… - arxiv preprint arxiv …, 2024 - arxiv.org
Large Language Models (LLMs) tend to be unreliable in the factuality of their answers. To
address this problem, NLP researchers have proposed a range of techniques to estimate …
address this problem, NLP researchers have proposed a range of techniques to estimate …
Incentive Distributed Knowledge Graph Market for Generative Artificial Intelligence in IoT
G Hao, Q Pan, J Wu - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Generative artificial intelligence (GAI) models are pre-trained using extensive public data.
However, in the Internet of Things (IoT) domain, distributed and heterogeneous data from …
However, in the Internet of Things (IoT) domain, distributed and heterogeneous data from …
SelfPrompt: Autonomously Evaluating LLM Robustness via Domain-Constrained Knowledge Guidelines and Refined Adversarial Prompts
Traditional methods for evaluating the robustness of large language models (LLMs) often
rely on standardized benchmarks, which can escalate costs and limit evaluations across …
rely on standardized benchmarks, which can escalate costs and limit evaluations across …
Benchmarking Biomedical Relation Knowledge in Large Language Models
As a special knowledge base (KB), a large language model (LLM) stores a great deal of
knowledge in the form of the parametric deep neural network, and evaluating the accuracy …
knowledge in the form of the parametric deep neural network, and evaluating the accuracy …