--- title: "Who cites QServe: W4A8KV4 Quantization — 114 citing papers" description: "114 papers of the Elamur Research library cite «QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving», found in their…" canonical: "https://research.elamur.ai/free/en/papers/lin-2024-qserve-w4a8kv4-quantization-system-co/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/lin-2024-qserve-w4a8kv4-quantization-system-co/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [QServe: W4A8KV4 Quantization and System Co-design…](https://md.research.elamur.ai/free/en/papers/lin-2024-qserve-w4a8kv4-quantization-system-co/) / cited by # Who cites «QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving» 114 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving»](https://md.research.elamur.ai/free/en/papers/lin-2024-qserve-w4a8kv4-quantization-system-co/) 1. [**DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads arXiv:2410.10819**Guangxuan Xiao, Jiaming Tang, Jingwei Zuo, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2024-duoattention-efficient-long-context-llm/) 2. **[EfficientQAT: Efficient Quantization-Aware Training for Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-efficientqat-efficient-quantization-aware-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengzhao Chen, Wenqi Shao, Peng Xu, et al.*2025 · 82 citations* 3. **[SageAttention: Accurate 8-Bit Attention for Plug-and-play Inference Acceleration](https://md.research.elamur.ai/free/en/papers/zhang-2024-sageattention-accurate-8-bit-attention/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Jintao Zhang, Jia Wei, Haofeng Huang, et al.*2024 · 74 citations* 4. [**MagicPIG: LSH Sampling for Efficient LLM Generation arXiv:2410.16179**Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, et al.*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-magicpig-lsh-sampling-efficient-llm/) 5. [**XAttention: Block Sparse Attention with Antidiagonal Scoring arXiv:2503.16428**Ruyi Xu, Guangxuan Xiao, Haofeng Huang, et al.*2025 · 59 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-xattention-block-sparse-attention-antidiagonal/) 6. [**From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models arXiv:2406.16838**Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2024-decoding-meta-generation-inference-time/) 7. **[“Give Me BF16 or Give Me Death”? Accuracy-Performance Trade-Offs in LLM Quantization](https://md.research.elamur.ai/free/en/papers/kurtic-2025-give-me-bf16-or-give/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Eldar Kurtic, Alexandre Noll Marques, Shubhra Pandit, et al.*2025 · 21 citations* 8. **[ARCQuant: Boosting NVFP4 Quantization with Augmented Residual Channels for LLMs](https://md.research.elamur.ai/free/en/papers/meng-2026-arcquant-boosting-nvfp4-quantization-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoqian Meng, Yilun Luo, Yafei Zhao, et al.*2026 · 5 citations* 9. **[MixKVQ: Query-Aware Mixed-Precision KV Cache Quantization for Long-Context Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2026-mixkvq-query-aware-mixed-precision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tao Zhang, Ziqian Zeng, Hao Peng, et al.*2026 · 5 citations* 10. **[SharVeT: Similarity-aware Parameter Sharing with Vector-based Tuning for Efficient LLM Compression](https://md.research.elamur.ai/free/en/papers/yun-2026-sharvet-similarity-aware-parameter-sharing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jeongin Yun, Jaeri Lee, Jongjin Kim, et al.*2026 · 1 citation* 11. **[ACBQ: Adaptive Cross-Block Quantization of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-acbq-adaptive-cross-block-quantization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hailing Wang, Jianglin Lu, Yitian Zhang, et al.*2026* 12. **[Evaluating Cost-Efficiency of LLMs in a RAG Setup on Polish Wikipedia: Quality vs. Energy Consumption](https://md.research.elamur.ai/free/en/papers/smits-2026-evaluating-cost-efficiency-llms-rag/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Patrycja Smits, Tomasz Walkowiak*2026* 13. **[RRAtention: Dynamic Block Sparse Attention via Per-Head Round-Robin Shifts for Long-Context Inference](https://md.research.elamur.ai/free/en/papers/liu-2026-rratention-dynamic-block-sparse-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siran Liu, Guoxia Wang, Sa Wang, et al.*2026* 101 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/lin-2024-qserve-w4a8kv4-quantization-system-co/) — QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving