May 2026
Fixing LLM Writing with Distribution Fine-Tuning
SFT-trained models fail to match their training distribution at any sampler setting. DFT, a new post-training step, closes the gap: 49% better MMD, 63% better judge quality, and output with no overused-token fingerprint beyond human-to-human variation.