QwenLong-L1.5: Post-Training Recipe for Long-Context Reasoning and Memory Management
Describes the QwenLong-L1.5 post-training recipe for extending LLM context windows while keeping reasoning quality intact. The work focuses not just on positional encodings but also on memory management strategies and training curricula that keep long-context performance from collapsing. This is highly relevant for anyone trying to turn a baseline LLM into a stable long-context model without re‑training from scratch.
Weizhou Shen, Ziyi Yang