Large language models and large concept models in radiology: Present challenges, future directions, and critical perspectives

Table 1 Methodological comparison of standard large language models and large concept models

Feature	LLMs	LCMs
Level of abstraction	Token-level prediction (word/sub word)	Concept-level prediction (sentence/idea)
Input representation	Processes individual tokens, language-specific	Uses sentence embeddings, language-agnostic
Reasoning and planning	Focuses on local predictions, lacks structured reasoning	Explicitly models hierarchical reasoning and structured planning
Zero-shot generalization	Requires fine-tuning for new tasks/Languages	Strong zero-shot learning across languages and modalities
Architectural modularity	Monolithic transformer, hard to modify	Modular design, allows easy extension and updates

LLM: Large language model; LCM: Large concept model.