---
title: "Who cites Yiran Ding — 127 papers of our library"
description: "127 papers of the Elamur Research library cite the works of Yiran Ding, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yiran-ding/cited-by/"
---
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# Who cites Yiran Ding

127 citations of their works from 127 papers of our library (of the 149,439 whose bibliographies we read) · 34 with a page here, the most cited first · [← Yiran Ding](https://md.research.elamur.ai/free/en/authors/yiran-ding/)

1. [**Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone arXiv:2404.14219**Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.*2024 · 1,134 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2024-phi-3-technical-report-highly/)
2. [**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/)
3. **[HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models](https://md.research.elamur.ai/free/en/papers/gutierrez-2024-hipporag-neurobiologically-inspired-long-term/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Bernal Jimenez Gutierrez, Yiheng Shu, Yu Gu, et al.*2024 · 268 citations*
4. **[Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models](https://md.research.elamur.ai/free/en/papers/levy-2024-same-task-more-tokens-impact/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mosh Levy, Alon Jacoby, Yoav Goldberg*2024 · 217 citations*
5. **[MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention](https://md.research.elamur.ai/free/en/papers/jiang-2024-minference-1-0-accelerating-pre/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, et al.*2024 · 202 citations*
6. [**PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling arXiv:2406.02069**Zefan Cai, Yichi Zhang, Bofei Gao, et al.*2024 · 155 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-pyramidkv-dynamic-kv-cache-compression/)
7. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs arXiv:2503.01743**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 152 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
8. [**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/)
9. **[InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory](https://md.research.elamur.ai/free/en/papers/xiao-2024-infllm-training-free-long-context/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chaojun Xiao, Pengle Zhang, Xu Han, et al.*2024 · 126 citations*
10. **[Make Your LLM Fully Utilize the Context](https://md.research.elamur.ai/free/en/papers/an-2024-make-llm-fully-utilize-context/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shengnan An, Zexiong Ma, Zeqi Lin, et al.*2024 · 97 citations*
11. **[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*
12. **[How to Train Long-Context Language Models (Effectively)](https://md.research.elamur.ai/free/en/papers/gao-2025-how-train-long-context-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Gao, Alexander Wettig, Howard Yen, et al.*2025 · 89 citations*
13. [**Long Context Transfer from Language to Vision arXiv:2406.16852**Peiyuan Zhang, Kaichen Zhang, Bo Li, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-long-context-transfer-language-vision/)
14. [**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/)
15. [**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/)
16. [**Long Context Compression with Activation Beacon arXiv:2401.03462**Peitian Zhang, Zheng Liu, Shitao Xiao, et al.*2024 · 47 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-long-context-compression-activation-beacon/)
17. **[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*
18. [**MiniCPM4: Ultra-Efficient LLMs on End Devices arXiv:2506.07900**MiniCPM Team, Chaojun Xiao, Yuxuan Li, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/minicpm-team-2025-minicpm4-ultra-efficient-llms/)
19. **[What are the Essential Factors in Crafting Effective Long Context Multi-Hop Instruction Datasets? Insights and Best Practices](https://md.research.elamur.ai/free/en/papers/chen-2025-what-are-essential-factors-crafting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhi Chen, Qiguang Chen, Libo Qin, et al.*2025 · 15 citations*
20. **[Evaluating Multilingual Long-Context Models for Retrieval and Reasoning](https://md.research.elamur.ai/free/en/papers/agrawal-2024-evaluating-multilingual-long-context-models/) [Workshop on Multilingual Representation Learning](https://md.research.elamur.ai/free/en/venues/mrl/)**Ameeta Agrawal, Andy Dang, Sina Bagheri Nezhad, et al.*2024 · 13 citations*
21. **[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*
22. **[MultiFileTest: A Multi-File-Level LLM Unit Test Generation Benchmark and Impact of Error Fixing Mechanisms](https://md.research.elamur.ai/free/en/papers/wang-2026-multifiletest-multi-file-level-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Wang, Congying Xia, Wenting Zhao, et al.*2026 · 2 citations*
23. **[Agentic Very Long Video Understanding](https://md.research.elamur.ai/free/en/papers/rege-2026-agentic-very-long-video-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aniket Rege, Arka Sadhu, Yuliang Li, et al.*2026 · 1 citation*
24. **[COMPASS: Enhancing Agent Long-Horizon Reasoning with Evolving Context](https://md.research.elamur.ai/free/en/papers/wan-2026-compass-enhancing-agent-long-horizon/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guangya Wan, Mingyang Ling, Xiaoqi Ren, et al.*2026 · 1 citation*
25. **[KG-MuLQA: A Framework for KG-based Multi-Level QA Extraction and Long-Context LLM Evaluation](https://md.research.elamur.ai/free/en/papers/tatarinov-2026-kg-mulqa-framework-kg-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nikita Tatarinov, Vidhyakshaya Kannan, Haricharana Srinivasa, et al.*2026 · 1 citation*
26. **[Adaptive Zooming via Relevance-Informed Positional Resource Allocation for Training-free LLM Context Extension](https://md.research.elamur.ai/free/en/papers/zhao-2026-adaptive-zooming-relevance-informed-positional/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongbo Zhao, Huibin Wang, Bin Tang, et al.*2026*
27. **[Can Calibration of Positional Encodings Enhance Long Context Utilization?](https://md.research.elamur.ai/free/en/papers/zehle-2026-can-calibration-positional-encodings-enhance/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tom Zehle, Matthias Aßenmacher*2026*
28. **[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*
29. **[HiGoE: Hierarchical Graph of Evidence to Enhance Retrieval-Augmented Generation for Long-context Summarization](https://md.research.elamur.ai/free/en/papers/yuan-2026-higoe-hierarchical-graph-evidence-enhance/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Long Yuan, Kaiwen Tian, Zi Chen, et al.*2026*
30. **[MemCoRL: Alternating Co-Optimization of Memory Retrieval and Utilization via Collaborative Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-memcorl-alternating-co-optimization-memory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuewen Liu, Peng Xu, Muxi Diao, et al.*2026*
31. **[NeedleChain: Measuring Intact Context Comprehension Capability of Large Language Models](https://md.research.elamur.ai/free/en/papers/moon-2026-needlechain-measuring-intact-context-comprehension/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hyeonseok Moon, Heuiseok Lim*2026*
32. **[Position Encoding with Random Float Sampling Enhances Length Generalization of Transformers](https://md.research.elamur.ai/free/en/papers/shimizu-2026-position-encoding-random-float-sampling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Atsushi Shimizu, Shohei Taniguchi, Yutaka Matsuo*2026*
33. **[Think Before you Write: QA-Guided Reasoning for Character Descriptions in Books](https://md.research.elamur.ai/free/en/papers/papoudakis-2026-think-before-you-write-qa/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Argyrios Papoudakis, Mirella Lapata, Frank Keller*2026*
34. **[When Efficiency Meets Safety: A Benchmark Security Analysis of KV Cache Compression in Large Language Models](https://md.research.elamur.ai/free/en/papers/ma-2026-when-efficiency-meets-safety-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoxiao Ma, Kuofeng Gao, Zeyi Lu, et al.*2026*

93 more citing papers of our library have no page here yet.

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