OnlineQAT: On-Policy Distillation for Ultra-Low-Bit Large Language Models.

arXiv:2610.09346v1 Announce Type: cross Abstract: Quantization-aware training (QAT) can recover much of the accuracy lost when large language models are compressed below four bits. Existing re- covery stages, however, are commonly optimized on fixed completion