--- title: "Who cites From 128K to 4M: Efficient Training — 5 citing papers" description: "5 papers of the Elamur Research library cite «From 128K to 4M: Efficient Training of Ultra-Long Context Large Language Models», found in their…" canonical: "https://research.elamur.ai/free/en/papers/xu-2026-128k-4m-efficient-training-ultra/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/xu-2026-128k-4m-efficient-training-ultra/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [From 128K to 4M: Efficient Training of Ultra-Long…](https://md.research.elamur.ai/free/en/papers/xu-2026-128k-4m-efficient-training-ultra/) / cited by # Who cites «From 128K to 4M: Efficient Training of Ultra-Long Context Large Language Models» 5 papers of our library cite it (of the 149,439 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «From 128K to 4M: Efficient Training of Ultra-Long Context Large Language Models»](https://md.research.elamur.ai/free/en/papers/xu-2026-128k-4m-efficient-training-ultra/) 1. **[Beyond Many-Shot Translation: Scaling In-Context Demonstrations For Low-Resource Machine Translation](https://md.research.elamur.ai/free/en/papers/salim-2026-beyond-many-shot-translation-scaling/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Luis Frentzen Salim, Esteban Carlin, Alexandre Morinvil, et al.*2026 · 2 citations* 2. **[Scaling External Knowledge Input Beyond Context Windows of LLMs via Multi-Agent Collaboration](https://md.research.elamur.ai/free/en/papers/liu-2026-scaling-external-knowledge-input-beyond/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zijun Liu, Zhennan Wan, Peng Li, et al.*2026 · 1 citation* 3 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/xu-2026-128k-4m-efficient-training-ultra/) — From 128K to 4M: Efficient Training of Ultra-Long Context Large Language Models