Knowledge Tree
GPT-3
Also known as: GPT-3 175B
Facts (21)
Sources
A survey on augmenting knowledge graphs (KGs) with large ... link.springer.com Nov 4, 2024 8 facts
claimThe OpenAI Generative Pre-trained Transformer (GPT) series, including GPT-2, GPT-3, and GPT-4, established standards for Natural Language Processing.
measurementGPT-3 contains 175 billion parameters and is capable of generating text, translating passages, and producing summaries of long articles.
claimGPT-3 performs a wide range of natural language processing (NLP) tasks without prior training using natural language instructions.
claimOpenAI's GPT-3 is designed to create coherent, relevant text, while Google's BERT focuses on understanding words in their context for NLP tasks.
claimLarge language models (LLMs) are defined as models containing between ten billion and one hundred billion parameters, with examples including GPT-3 and PaLM.
claimBERT and GPT-3 models have been employed to generate and optimize database queries, providing a user-friendly interface and enhancing query performance, as noted in [54].
measurementOpenAI's GPT-3 model contains 175 billion parameters and is known for high-quality text generation, translation, question answering, and summarization.
claimFoundation models are trained without specific instructions for their use cases, as exemplified by GPT-3.
Building Trustworthy NeuroSymbolic AI Systems - arXiv arxiv.org 3 facts
claimPrompt injection or adversarial prompting can override the attention of Large Language Models to previous instructions and force them to act on the current prompt, an issue that has affected GPT-3 (Branch et al. 2022).
accountGPT-3 demonstrated potential downsides in health-specific question-answering when it responded to a user's question about self-harm with the advice, "Yes, you should," as reported by Daws (2023).
accountR. Daws reported in 2020 that a medical chatbot using OpenAI’s GPT-3 told a fake patient to kill themselves.
The construction and refined extraction techniques of knowledge ... nature.com Feb 10, 2026 2 facts
claimThe large language model GPT-3 has shown near-expert performance in open-domain relation extraction, particularly in handling long-tail semantics, outperforming supervised models.
measurementHu et al. applied LoRA to the GPT-3 175B model, which reduced the number of trainable parameters by 10,000 times while maintaining inference speed.
A Survey on the Theory and Mechanism of Large Language Models arxiv.org Mar 12, 2026 2 facts
referenceWei et al. (2023) conducted an exploration of in-context learning (ICL) using GPT-3, InstructGPT, Codex, PaLM, and Flan-PaLM across different configurations.
claimMin et al. (2022a) found that replacing labels in input-label pairs with random ones during in-context learning inference results in only marginal decreases in performance across 12 models, including GPT-3, which contrasts with findings by Xie et al. (2021).
How Enterprise AI, powered by Knowledge Graphs, is ... blog.metaphacts.com Oct 7, 2025 1 fact
measurementOpenAI found that the GPT-3 large language model produced hallucinations, defined as authoritative-sounding but factually incorrect or fabricated responses, approximately 15% of the time.
Medical Hallucination in Foundation Models and Their ... medrxiv.org Mar 3, 2025 1 fact
claimPretrained Large Language Models such as GPT-3, GPT-4, PaLM, LLaMA, and BERT have demonstrated advancements due to the extensive datasets used in their training.
Neuro-symbolic AI - Wikipedia en.wikipedia.org 1 fact
referenceThe 'Symbolic' approach in neuro-symbolic integration is used by many neural models in natural language processing, such as BERT, RoBERTa, and GPT-3, where words or subword tokens serve as the ultimate input and output.
Combining Knowledge Graphs and Large Language Models - arXiv arxiv.org Jul 9, 2024 1 fact
measurementOpenAI released GPT-3 in 2020, which features 175 billion parameters.
Combining large language models with enterprise knowledge graphs frontiersin.org Aug 26, 2024 1 fact
claimLarge Language Models, such as GPT-3, struggle with specific information extraction tasks, including managing sentences that do not contain named entities or relations (Gutierrez et al., 2022).
David Chalmers - Wikipedia en.wikipedia.org 1 fact
quoteDavid Chalmers described GPT-3 as "one of the most interesting and important AI systems ever produced" in a 2020 Daily Nous series.