Large Language Models ↔ Transformer models

Relations (1)

related 2.00 — strongly supporting 3 facts

Large Language Models and Transformer models are related because Transformer models serve as the foundational architecture for modern LLMs as established in [1]. Furthermore, both are categorized as generative AI models that utilize neural networks to learn patterns for output generation [2], and Transformer models are specifically employed to evaluate the performance and accuracy of LLMs [3].

Facts (3)

Sources

Real-Time Evaluation Models for RAG: Who Detects Hallucinations ... cleanlab.ai Cleanlab 1 fact

referenceThe Hughes Hallucination Evaluation Model (HHEM) is a Transformer model trained by Vectara to distinguish between hallucinated and correct responses from various Large Language Models across different context and response data.

Neuro-Symbolic AI: Explainability, Challenges & Future Trends linkedin.com Ali Rouhanifar · LinkedIn 1 fact

claimGenerative AI models, including Large Language Models (LLMs), Generative Adversarial Networks (GANs), and Transformer models, function by training neural networks on vast datasets to learn underlying patterns, which enables the generation of new outputs.

A survey on augmenting knowledge graphs (KGs) with large ... link.springer.com Springer 1 fact

claimVaswani et al. introduced transformer models in 2017, which serve as the foundation for modern LLMs such as BERT and GPT.