---
title: "Who cites Landmark Attention: — 85 citing papers"
description: "85 papers of the Elamur Research library cite «Landmark Attention: Random-Access Infinite Context Length for Transformers», found in their…"
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---
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# Who cites «Landmark Attention: Random-Access Infinite Context Length for Transformers»

85 papers of our library cite it (of the 149,439 whose bibliographies we read) · 26 with a page here, the most cited first · [← back to «Landmark Attention: Random-Access Infinite Context Length for Transformers»](https://md.research.elamur.ai/free/en/papers/mohtashami-2023-landmark-attention-random-access-infinite/)

1. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
2. [**LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding arXiv:2308.14508**Yushi Bai, Xin Lv, Jiajie Zhang, et al.*2023 · 514 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-longbench-bilingual-multitask-benchmark/)
3. **[Improving Text Embeddings with Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-improving-text-embeddings-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liang Wang, Nan Yang, Xiaolong Huang, et al.*2024 · 437 citations*
4. [**RULER: What's the Real Context Size of Your Long-Context Language Models? arXiv:2404.06654**Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.*2024 · 400 citations*](https://md.research.elamur.ai/free/en/papers/hsieh-2024-ruler-s-real-context-size/)
5. **[KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization](https://md.research.elamur.ai/free/en/papers/hooper-2024-kvquant-towards-10-million-context/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh, et al.*2024 · 294 citations*
6. [**LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models arXiv:2309.12307**Yukang Chen, Shengju Qian, Haotian Tang, et al.*2023 · 268 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-longlora-efficient-fine-tuning-long/)
7. [**KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache arXiv:2402.02750**Zirui Liu, Jiayi Yuan, Hongye Jin, et al.*2024 · 244 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-kivi-tuning-free-asymmetric-2bit/)
8. [**Effective Long-Context Scaling of Foundation Models arXiv:2309.16039**Wenhan Xiong, Jingyu Liu, Igor Molybog, et al.*2023 · 184 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-effective-long-context-scaling-foundation/)
9. [**L-Eval: Instituting Standardized Evaluation for Long Context Language Models arXiv:2307.11088**Chenxin An, Shansan Gong, Ming Zhong, et al.*2023 · 161 citations*](https://md.research.elamur.ai/free/en/papers/an-2023-l-eval-instituting-standardized-evaluation/)
10. [**LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens arXiv:2402.13753**Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, et al.*2024 · 142 citations*](https://md.research.elamur.ai/free/en/papers/ding-2024-longrope-extending-llm-context/)
11. [**Long-context LLMs Struggle with Long In-context Learning arXiv:2404.02060**Tianle Li, Ge Zhang, Quy Duc Do, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-long-context-llms-struggle-long/)
12. [**Retrieval meets Long Context Large Language Models arXiv:2310.03025**Peng Xu, Wei Ping, Xianchao Wu, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-retrieval-meets-long-context-large/)
13. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/)
14. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations*
15. **[Chain of Agents: Large Language Models Collaborating on Long-Context Tasks](https://md.research.elamur.ai/free/en/papers/zhang-2024-chain-agents-large-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yusen Zhang, Ruoxi Sun, Yanfei Chen, et al.*2024 · 104 citations*
16. **[LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models](https://md.research.elamur.ai/free/en/papers/han-2024-lm-infinite-zero-shot-extreme/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chi Han, Qifan Wang, Hao Peng, et al.*2024 · 95 citations*
17. [**LLM Inference Unveiled: Survey and Roofline Model Insights arXiv 2024**Zhihang Yuan, Yuzhang Shang, Yang Zhou, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2024-llm-inference-unveiled-survey-roofline/)
18. [**LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning arXiv:2401.01325**Hongye Jin, Xiaotian Han, Jingfeng Yang, et al.*2024 · 81 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-llm-maybe-longlm-self-extend/)
19. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
20. [**Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling arXiv:2406.07522**Liliang Ren, Yang Liu, Yadong Lu, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/ren-2024-samba-simple-hybrid-state-space/)
21. [**PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training arXiv:2309.10400**Dawei Zhu, Nan Yang, Liang Wang, et al.*2023 · 52 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-pose-efficient-context-window/)
22. **[LongEmbed: Extending Embedding Models for Long Context Retrieval](https://md.research.elamur.ai/free/en/papers/zhu-2024-longembed-extending-embedding-models-long/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Dawei Zhu, Liang Wang, Nan Yang, et al.*2024 · 37 citations*
23. **[ProxyQA: An Alternative Framework for Evaluating Long-Form Text Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/tan-2024-proxyqa-alternative-framework-evaluating-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haochen Tan, Zhijiang Guo, Zhan Shi, et al.*2024 · 30 citations*
24. **[On Many-Shot In-Context Learning for Long-Context Evaluation](https://md.research.elamur.ai/free/en/papers/zou-2025-many-shot-context-learning-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kaijian Zou, Muhammad Khalifa, Lu Wang*2025 · 8 citations*
25. **[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/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chejian Xu, Wei Ping, Peng Xu, et al.*2026 · 5 citations*
26. **[From Logical to Computational Sparsity: Structure-Aware Block-Sparse Attention for Long-Code Completion](https://md.research.elamur.ai/free/en/papers/wang-2026-logical-computational-sparsity-structure-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanli Wang, Yanlin Wang, Bowen Zhang, et al.*2026*

59 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/mohtashami-2023-landmark-attention-random-access-infinite/) — Landmark Attention: Random-Access Infinite Context Length for Transformers