Abstract
Jet-Long is a tuning-free method for extending the context length of large language models. It combines a local RoPE-faithful window with a dynamically rescaled long-range window and an efficient attention implementation, preserving short-context behavior while supporting longer inputs without retraining.
Type
Publication
Advances in Neural Information Processing Systems (NeurIPS 2026), accepted
