How LLMs Work: Probabilistic Word Generation and Dual Training-Inference Components
LLMs generate text word by word based on probabilities conditioned on prior words. Their core task of converting prompts to answers is achieved through language imitation and human quality ratings, with separate inference and training components.
2026-08-26 ~ 2026-08-26 · 2 related posts
- LLMs explained: Neural networks that convert prompts to answers via training and inference — KordingLab · 2026-08-26
- LLM Core Mechanics: Probability-Based Word-by-Word Generation — KordingLab · 2026-08-26