Transformers ↔ Large Language Models

Relations (1)

related 2.81 — strongly supporting 6 facts

Large Language Models are fundamentally built upon transformer architectures, which provide the necessary mechanisms for attention and parameter scaling as described in [1], [2], and [3]. Furthermore, the relationship is highlighted by their shared categorization within Generative AI [4] and their joint application in specialized research fields like genomics [5].

Facts (6)

Sources

The Synergy of Symbolic and Connectionist AI in LLM ... arxiv.org arXiv 1 fact

claimLarge Language Models are trained on large-scale transformers comprising billions of learnable parameters to support abilities including perception, reasoning, planning, and action.

Combining Knowledge Graphs and Large Language Models - arXiv arxiv.org arXiv 1 fact

referenceMicaela E. Consens, Cameron Dufault, Michael Wainberg, Duncan Forster, Mehran Karimzadeh, Hani Goodarzi, Fabian J. Theis, Alan Moses, and Bo Wang authored the 2023 paper 'To transformers and beyond: Large language models for the genome' (arXiv:2311.07621).

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

claimThe architecture of large language models, utilizing attention and transformers, allows them to identify important words in sentences, enabling them to handle a wide range of NLP tasks.

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

claimKnowledge of Generative AI architectures, such as Large Language Models (LLMs), Generative Adversarial Networks (GANs), and Transformers, is critical for driving innovation, enhancing productivity, and personalizing experiences in industries like marketing, software development, and design.

The Synergy of Symbolic and Connectionist AI in LLM-Empowered ... arxiv.org arXiv 1 fact

claimLarge Language Models (LLMs) are trained on large-scale transformers comprising billions of learnable parameters to support agent abilities such as perception, reasoning, planning, and action.

Building Trustworthy NeuroSymbolic AI Systems - arXiv arxiv.org arXiv 1 fact

claimLarge Language Models (LLMs) are successors to foundational language models like BERT (Bidirectional Encoder Representations from Transformers) and represent a combination of feedforward neural networks and transformers.