--- title: "Who cites Ivan Rodkin — 77 papers of our library" description: "77 papers of the Elamur Research library cite the works of Ivan Rodkin, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/ivan-rodkin/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ivan-rodkin/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Ivan Rodkin](https://md.research.elamur.ai/free/en/authors/ivan-rodkin/) / cited by # Who cites Ivan Rodkin 80 citations of their works from 77 papers of our library (of the 149,439 whose bibliographies we read) · 19 with a page here, the most cited first · [← Ivan Rodkin](https://md.research.elamur.ai/free/en/authors/ivan-rodkin/) 1. [**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/) 2. [**LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks arXiv:2412.15204**Yushi Bai, Shangqing Tu, Jiajie Zhang, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-longbench-v2-deeper-understanding/) 3. **[BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack](https://md.research.elamur.ai/free/en/papers/kuratov-2024-babilong-testing-limits-llms-long/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuri Kuratov, Aydar Bulatov, Petr Anokhin, et al.*2024 · 88 citations* 4. [**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/) 5. [**Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries arXiv:2409.12640**Kiran Vodrahalli; Santiago Ontanon; Nilesh Tripuraneni; Kelvin Xu; Sanil Jain; Rakesh Shivanna; Jeffrey Hui; Nishanth Dikkala; Mehran Kazemi; Bahare Fatemi; Rohan Anil; Ethan Dyer; Siamak Shakeri; Roopali Vij; Harsh Mehta; Vinay Ramasesh; Quoc Le; Ed Chi; Yifeng Lu; Orhan Firat; Angeliki Lazaridou; Jean-Baptiste Lespiau; Nithya Attaluri;, Kate Olszewska*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/vodrahalli-2024-michelangelo-long-context-evaluations-haystacks/) 6. [**InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language Models arXiv:2503.06692**Yuchen Yan, Yongliang Shen, Yang Liu, et al.*2025 · 29 citations*](https://md.research.elamur.ai/free/en/papers/yan-2025-inftythink-breaking-length-limits-long/) 7. [**GSM-Infinite: How Do Your LLMs Behave over Infinitely Increasing Context Length and Reasoning Complexity? arXiv:2502.05252**Yang Zhou, Hongyi Liu, Zhuoming Chen, et al.*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2025-gsm-infinite-llms-behave-over/) 8. **[POSITION BIAS MITIGATES POSITION BIAS: Mitigate Position Bias Through Inter-Position Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/wang-2025-position-bias-mitigates-position-bias/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yifei Wang, Feng Xiong, Yong Wang, et al.*2025 · 13 citations* 9. **[DARS: Dynamic Action Re-Sampling to Enhance Coding Agent Performance by Adaptive Tree Traversal](https://md.research.elamur.ai/free/en/papers/aggarwal-2025-dars-dynamic-action-re-sampling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vaibhav Aggarwal, Ojasv Kamal, Abhinav Japesh, et al.*2025 · 4 citations* 10. **[From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms](https://md.research.elamur.ai/free/en/papers/luo-2026-storage-experience-survey-evolution-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinghao Luo, Yuchen Tian, Chuxue Cao, et al.*2026 · 3 citations* 11. **[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* 12. **[SepSeq: A Training-Free Framework for Long Numerical Sequence Processing in LLMs](https://md.research.elamur.ai/free/en/papers/sun-2026-sepseq-training-free-framework-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jie Sun, Yu Liu, Lu Han, et al.*2026 · 1 citation* 13. **[Beyond Memorization: Extending Reasoning Depth with Recurrence, Memory and Test-Time Compute Scaling](https://md.research.elamur.ai/free/en/papers/rodkin-2026-beyond-memorization-extending-reasoning-depth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ivan Rodkin, Daniil Orel, Konstantin Smirnov, et al.*2026* 14. **[CoMeT: Collaborative Memory Transformer for Efficient Long Context Modeling](https://md.research.elamur.ai/free/en/papers/zhao-2026-comet-collaborative-memory-transformer-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Runsong Zhao, Shilei Liu, Jiwei Tang, et al.*2026* 15. **[Data Foundations of Long-Context Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/sun-2026-data-foundations-long-context-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zechen Sun, Yuyang Sun, Zhaochen Su, et al.*2026* 16. **[Decoupled Reasoning with Implicit Fact Tokens (DRIFT): A Dual-Model Framework for Efficient Long-Context Inference](https://md.research.elamur.ai/free/en/papers/xie-2026-decoupled-reasoning-implicit-fact-tokens/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenxuan Xie, Xuhong Wang*2026* 17. **[Distilling Long-CoT Reasoning through Collaborative Step-wise Multi-Teacher Decoding](https://md.research.elamur.ai/free/en/papers/yun-2026-distilling-long-cot-reasoning-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Taewon Yun, Jisu Shin, Jeonghwan Choi, et al.*2026* 18. **[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* 19. **[Sense and Sensitivity: Examining the Influence of Semantic Recall on Long Context Code Understanding](https://md.research.elamur.ai/free/en/papers/storek-2026-sense-sensitivity-examining-influence-semantic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Adam Štorek, Mukur Gupta, Samira Hajizadeh, et al.*2026* 58 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/ivan-rodkin/) — Ivan Rodkin