---
title: "Who cites FlashInfer: Efficient and — 173 citing papers"
description: "173 papers of the Elamur Research library cite «FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving», found in their…"
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---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [FlashInfer: Efficient and Customizable Attention…](https://md.research.elamur.ai/free/en/papers/ye-2025-flashinfer-efficient-customizable-attention-engine/) / cited by

# Who cites «FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving»

173 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving»](https://md.research.elamur.ai/free/en/papers/ye-2025-flashinfer-efficient-customizable-attention-engine/)

1. **[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*
2. **[AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning](https://md.research.elamur.ai/free/en/papers/fu-2025-areal-large-scale-asynchronous-reinforcement/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wei Fu, Jiaxuan Gao, Xujie Shen, et al.*2025 · 80 citations*
3. [**Kevin: Multi-Turn RL for Generating CUDA Kernels arXiv 2025**Carlo Baronio, Pietro Marsella, Ben Pan, et al.*2025 · 69 citations*](https://md.research.elamur.ai/free/en/papers/baronio-2025-kevin-multi-turn-rl-generating/)
4. **[Deep Kernel Fusion for Transformers](https://md.research.elamur.ai/free/en/papers/zhang-2026-deep-kernel-fusion-transformers/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zixi Zhang, Zhiwen Mo, Yiren Zhao, et al.*2026 · 1 citation*
5. **[DELTA: Dynamic Layer-Aware Token Attention for Efficient Long-Context Reasoning](https://md.research.elamur.ai/free/en/papers/zarch-2026-delta-dynamic-layer-aware-token/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hossein Entezari Zarch, Lei Gao, Chaoyi Jiang, et al.*2026 · 1 citation*
6. **[HeteroCache: A Dynamic Retrieval Approach to Heterogeneous KV Cache Compression for Long-Context LLM Inference](https://md.research.elamur.ai/free/en/papers/shi-2026-heterocache-dynamic-retrieval-approach-heterogeneous/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyuan Shi, Qibo Qiu, Xuefeng, et al.*2026*
7. **[Reducing Token Redundancy in LVLMs: A Systematic Review of Token Pruning Methods](https://md.research.elamur.ai/free/en/papers/yuan-2026-reducing-token-redundancy-lvlms-systematic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanzhang Yuan, Mengxuan Hu, Wenhao Zhang, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/ye-2025-flashinfer-efficient-customizable-attention-engine/) — FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving