LLMs have excelled at token-level processing but fall short when it comes to hierarchical reasoning and long-form coherence—essential traits of human intelligence.
Meta’s Large Concept Models (LCMs) flip the script by operating at the sentence level in a language-agnostic, high-dimensional embedding space.
Instead of token-based predictions, LCMs use “concepts” (think semantic ideas, not just words), enabling them to:
🔹 Plan outputs with explicit hierarchical structures
🔹 Handle long contexts more efficiently
🔹 Generalize across 200 languages without retraining
This architecture is designed to mirror how humans think—by reasoning abstractly rather than word-by-word.
GitHub – facebookresearch/large_concept_model: Large Concept Models: Language modeling in a sentence representation space
Large Concept Models: Language modeling in a sentence representation space – facebookresearch/large_concept_model