新位置编码突破序列距离限制，实现跨模态距离不变性，为多模态Transformer带来更优位置感知。
arXiv:2603.10863v2 Announce Type: replace Abstract: Despite the remarkable capabilities of Multimodal Large Language Models (MLLMs), they still suffer…
一种随机化YaRN方法，破解长上下文推理外推难题，实验显示显著提升长度泛化能力。
arXiv:2606.23687v1 Announce Type: new Abstract: Large language models (LLMs) are typically pretrained on short sequences and then extended to work on …
新方法RePo让大模型重新调整上下文位置，提升长文本理解与推理能力。
arXiv:2512.14391v3 Announce Type: replace-cross Abstract: In-context learning is fundamental to modern Large Language Models (LLMs); however, prevaili…
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…