直击长上下文推理痛点，用RoPE对齐剪枝实现KV-Cache压缩，兼顾效率与精度。
arXiv:2602.02599v4 Announce Type: replace-cross Abstract: Long-context inference in large language models (LLMs) is bottlenecked by the memory and com…
提出Periodic RoPE方法，让大模型突破上下文长度瓶颈，实现无限长序列理解，是长文本处理的重要进步。
arXiv:2605.27980v1 Announce Type: cross Abstract: The ability to process ultra-long contexts is crucial for large language models (LLMs) to perform lo…
提出针对AI智能体不确定性量化的适当评分规则，优化模型可信度评估，理论扎实且具实践价值。
arXiv:2605.24756v1 Announce Type: new Abstract: Language-model agents increasingly emit uncertainty signals throughout a trajectory, but existing agen…