---
title: "Who cites Zachary Ankner — 93 papers of our library"
description: "93 papers of the Elamur Research library cite the works of Zachary Ankner, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/zachary-ankner/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zachary-ankner/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Zachary Ankner](https://md.research.elamur.ai/free/en/authors/zachary-ankner/) / cited by

# Who cites Zachary Ankner

93 citations of their works from 93 papers of our library (of the 149,439 whose bibliographies we read) · 28 with a page here, the most cited first · [← Zachary Ankner](https://md.research.elamur.ai/free/en/authors/zachary-ankner/)

1. **[s1: Simple test-time scaling](https://md.research.elamur.ai/free/en/papers/muennighoff-2025-s1-simple-test-time-scaling/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.*2025 · 608 citations*
2. [**Kimi k1.5: Scaling Reinforcement Learning with LLMs arXiv:2501.12599**Kimi Team, Angang Du, Bofei Gao, et al.*2025 · 431 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k1-5-scaling-reinforcement/)
3. **[FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision](https://md.research.elamur.ai/free/en/papers/shah-2024-flashattention-3-fast-accurate-attention/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jay Shah, Ganesh Bikshandi, Ying Zhang, et al.*2024 · 400 citations*
4. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
5. [**Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving FAST 2025**Ruoyu Qin, Zheming Li, Weiran He, et al.*2024 · 161 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-mooncake-kvcache-centric-disaggregated-architecture/)
6. [**Generative Verifiers: Reward Modeling as Next-Token Prediction arXiv:2408.15240**Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.*2024 · 152 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-generative-verifiers-reward-modeling-as/)
7. **[LoongServe: Efficiently Serving Long-Context Large Language Models with Elastic Sequence Parallelism](https://md.research.elamur.ai/free/en/papers/wu-2024-loongserve-efficiently-serving-long-context/) [ACM SIGOPS Symposium on Operating Systems Principles (SOSP)](https://md.research.elamur.ai/free/en/venues/acm-sigops-symposium-on-operating-systems-principles-sosp/)**Bingyang Wu, Shengyu Liu, Yinmin Zhong, et al.*2024 · 131 citations*
8. **[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*
9. [**World Model on Million-Length Video And Language With Blockwise RingAttention arXiv:2402.08268**Hao Liu, Wilson Yan, Matei Zaharia, et al.*2024 · 99 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-world-model-million-length-video/)
10. [**Inference-Time Scaling for Generalist Reward Modeling arXiv:2504.02495**Zijun Liu, Peiyi Wang, Runxin Xu, et al.*2025 · 65 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-inference-time-scaling-generalist/)
11. [**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/)
12. [**Generative Reward Models arXiv:2410.12832**Dakota Mahan, Duy Van Phung, Rafael Rafailov, et al.*2024 · 58 citations*](https://md.research.elamur.ai/free/en/papers/mahan-2024-generative-reward-models/)
13. [**AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset arXiv:2504.16891**Ivan Moshkov, Darragh Hanley, Ivan Sorokin, et al.*2025 · 50 citations*](https://md.research.elamur.ai/free/en/papers/moshkov-2025-aimo-2-winning-solution-building/)
14. [**RMB: Comprehensively Benchmarking Reward Models in LLM Alignment arXiv:2410.09893**Enyu Zhou, Guodong Zheng, Binghai Wang, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-rmb-comprehensively-benchmarking-reward-models/)
15. [**TICKing All the Boxes: Generated Checklists Improve LLM Evaluation and Generation arXiv:2410.03608**Jonathan Cook, Tim Rocktaschel, Jakob Foerster, et al.*2024 · 29 citations*](https://md.research.elamur.ai/free/en/papers/cook-2024-ticking-all-boxes-generated-checklists/)
16. **[A Survey on Large Language Models for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2025-survey-large-language-models-mathematical/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Peng-Yuan Wang, Tian-Shuo Liu, Chenyang Wang, et al.*2025 · 26 citations*
17. **[OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment](https://md.research.elamur.ai/free/en/papers/liu-2026-openrubrics-scalable-synthetic-rubric-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianci Liu, Ran Xu, Tony Yu, et al.*2026 · 25 citations*
18. [**Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation arXiv:2410.02725**Rohin Manvi, Anikait Singh, Stefano Ermon*2024 · 22 citations*](https://md.research.elamur.ai/free/en/papers/manvi-2024-adaptive-inference-time-compute-llms/)
19. [**Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models arXiv:2412.02980**Alex Havrilla, Andrew Dai, Laura O'Mahony, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-surveying-effects-quality-diversity-complexity/)
20. [**Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models arXiv:2503.24377**Rui Wang, Hongru Wang, Boyang Xue, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-harnessing-reasoning-economy-survey-efficient/)
21. [**When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning arXiv:2504.01005**Nishad Singhi, Hritik Bansal, Arian Hosseini, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/singhi-2025-solve-verify-compute-optimal-problem/)
22. [**mR3: Multilingual Rubric-Agnostic Reward Reasoning Models arXiv:2510.01146**David Anugraha, Shou-Yi Hung, Zilu Tang, et al.*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/anugraha-2025-mr3-multilingual-rubric-agnostic-reward/)
23. **[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*
24. **[Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-length-scaling-synergizing-breadth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiyuan Zhang, Yufei Wang, Tianhe Wu, et al.*2026*
25. **[JudgeAgent: Beyond Static Benchmarks for Knowledge-Driven and Dynamic LLM Evaluation](https://md.research.elamur.ai/free/en/papers/shi-2026-judgeagent-beyond-static-benchmarks-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhichao Shi, Xuhui Jiang, Chengjin Xu, et al.*2026*
26. **[PIRA: Preference-Oriented Instruction-Tuned Reward Models with Dual Aggregation](https://md.research.elamur.ai/free/en/papers/xue-2026-pira-preference-oriented-instruction-tuned/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yongfu Xue*2026*
27. **[Reward Modeling for Scientific Writing Evaluation](https://md.research.elamur.ai/free/en/papers/sahinuc-2026-reward-modeling-scientific-writing-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Furkan Şahinuç, Subhabrata Dutta, Iryna Gurevych*2026*
28. **[Simple Role Assignment is Extraordinarily Effective for Safety Alignment](https://md.research.elamur.ai/free/en/papers/ziheng-2026-simple-role-assignment-is-extraordinarily/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhou Ziheng, Jiakun Ding, Zhaowei Zhang, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/authors/zachary-ankner/) — Zachary Ankner