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Foundation Model

Definition
AI-generated

A foundation model is a large model trained broadly on data (often self-supervised) so it can be adapted downstream via fine-tuning, prompting, or retrieval; the term emphasizes reuse across tasks rather than a single narrow objective.

Topics
LLM and Agents
Related
Deep Learning Fine-Tuning Machine Learning

Why it matters in GWAS

Biomedical foundation models (text, protein sequence, or multimodal) are proposed for annotation, variant effect priors, and literature mining; claims should be checked against independent benchmarks and domain-specific gold standards.

Example usage

"The discussion contrasted a general text foundation model with a domain-fine-tuned model for extracting odds ratios from abstracts."

Deep Learning Fine-Tuning Machine Learning Neural Network Single-Cell Foundation Model Transfer Learning Genome-Wide Association Study (GWAS) In-Context Learning Large Language Model (LLM) LLM Hallucination Pretraining Prompt Engineering Retrieval-Augmented Generation (RAG)
Related-term network

Click any node to open that term page.

Node order. The current term is first. Next come every page linked from Related terms, in the same top-to-bottom order as that list. Then new terms appear in two-hop layers: for each of those direct neighbors (in that same order), their related terms are appended if not already listed. A third pass does the same for two-hop nodes. The walk stops when a fixed maximum number of nodes is reached.

References

  • Bommasani R, et al. (2021). On the opportunities and risks of foundation models. arXiv:2108.07258.
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