CORE-GPT: Combining Open Access Research and Large Language Models for Credible, Trustworthy Question Answering

2023/01/01 by David Pride, Matteo Cancellieri, Petr Knoth · 1 voice · 1 citation
Computer Science · Medicine · #Artificial Intelligence in Healthcare and Education #Machine Learning in Healthcare #Topic Modeling

paper · doi:10.1007/978-3-031-43849-3_13

crossref issued 2023/01/01 · crossref published 2023/01/01 · crossref published-print 2023/01/01 · openalex publication_date 2023/01/01 · crossref created 2023/09/21 · crossref published-online 2023/09/22 · crossref deposited 2024/10/28 · openalex created_date 2025/10/10 · crossref indexed 2026/06/03 · openalex updated_date 2026/07/29

Citations

• Artificial Hallucinations in ChatGPT: Implications in Scientific Writing
• ChatGPT for good? On opportunities and challenges of large language models for education

Cited by

• Towards automated evaluation of Arabic research: a study on the efficacy of large language models in analyzing the quality of Arabic academic papers

Discussions

• Yesterday at TPDL 2023 David Pride presented “CORE-GPT: Combining Open Access research and large language models for credible, trustworthy question answering” Pride’s prototype provides answers that [bsky, 1 points, 0 comments]