all AI news
Evaluating Text Summaries Generated by Large Language Models Using OpenAI's GPT
May 8, 2024, 4:42 a.m. | Hassan Shakil, Atqiya Munawara Mahi, Phuoc Nguyen, Zeydy Ortiz, Mamoun T. Mardini
cs.LG updates on arXiv.org arxiv.org
Abstract: This research examines the effectiveness of OpenAI's GPT models as independent evaluators of text summaries generated by six transformer-based models from Hugging Face: DistilBART, BERT, ProphetNet, T5, BART, and PEGASUS. We evaluated these summaries based on essential properties of high-quality summary - conciseness, relevance, coherence, and readability - using traditional metrics such as ROUGE and Latent Semantic Analysis (LSA). Uniquely, we also employed GPT not as a summarizer but as an evaluator, allowing it to …
abstract arxiv bart bert cs.ai cs.cl cs.lg face generated gpt gpt models hugging face independent language language models large language large language models openai quality research six summary text transformer transformer-based models type
More from arxiv.org / cs.LG updates on arXiv.org
Efficient Data-Driven MPC for Demand Response of Commercial Buildings
2 days, 19 hours ago |
arxiv.org
Testing the Segment Anything Model on radiology data
2 days, 19 hours ago |
arxiv.org
Calorimeter shower superresolution
2 days, 19 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Software Engineer for AI Training Data (School Specific)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Python)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Tier 2)
@ G2i Inc | Remote
Data Engineer
@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US