长上下文推理新突破，递归证据回放让LLM精准捕捉关键信息
arXiv:2607.02509v1 Announce Type: new Abstract: Understanding and reasoning over long contexts has become a key requirement for deploying large langua…
提出预测预填充方法，让扩散语言模型高效处理超长上下文，解码速度显著提升。
arXiv:2606.10537v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) re-encode the entire prefix at every denoising step, causing r…
提出 OBCache 最优脑剪枝方法，精准削减 KV 缓存，让长上下文大模型推理又快又省内存。
arXiv:2510.07651v2 Announce Type: replace-cross Abstract: Large language models (LLMs) with extended context windows enable powerful applications but …
LLM长上下文推理新突破：无需额外训练即可精准估计KV缓存重要性，大幅降低推理开销。
arXiv:2605.27740v1 Announce Type: new Abstract: Long-context inference in large language models (LLMs) is bottlenecked by the linear growth of the sel…