🔗 Who cites «LLM Inference Unveiled: Survey and Roofline Model Insights»

78 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · ← back to «LLM Inference Unveiled: Survey and Roofline Model Insights»

1. HybridFlow: A Flexible and Efficient RLHF FrameworkarXiv:2409.19256Guangming Sheng, Chi Zhang, Zilingfeng Ye, et al.2024 · 624 citations
2. A Survey on Efficient Inference for Large Language ModelsarXiv:2404.14294Zixuan Zhou, Xuefei Ning, Ke Hong, et al.2024 · 113 citations
3. EfficientQAT: Efficient Quantization-Aware Training for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mengzhao Chen, Wenqi Shao, Peng Xu, et al.2025 · 82 citations
4. MixKVQ: Query-Aware Mixed-Precision KV Cache Quantization for Long-Context ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Tao Zhang, Ziqian Zeng, Hao Peng, et al.2026 · 5 citations
5. Sparse Brains are Also Adaptive Brains: Cognitive-Load-Aware Dynamic Activation for LLMsFindings of the Association for Computational LinguisticsYiheng Yang, Yujie Wang, Chi Ma, et al.2026 · 3 citations
6. SSSD: Simply-Scalable Speculative DecodingAnnual Meeting of the Association for Computational Linguistics (ACL)Michele Marzollo, Jiawei Zhuang, Niklas Roemer, et al.2026 · 3 citations
7. Beyond Accuracy: Unveiling Inefficiency Patterns in Tool-Integrated ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Qisheng Su, Shiting Huang, Zhen Fang, et al.2026 · 2 citations
8. Benchmarking Post-Training Quantization of Large Language Models under Microscaling Floating Point FormatsAnnual Meeting of the Association for Computational Linguistics (ACL)Manyi Zhang, Ji-Fu Li, Zhongao Sun, et al.2026
9. Calibrating Inference Time Alignment with Sequence-level Risk AccumulationAnnual Meeting of the Association for Computational Linguistics (ACL)Shanwen Tan, Ziyang Dong, Wei Ju, et al.2026
10. COMPEL: Compensated Mixture-of-Experts Pruning with Expert-Layer distributionFindings of the Association for Computational LinguisticsSeohee Yoon, Yong Suk Choi2026
11. pQuant: Towards Effective Low-Bit Language Models via Decoupled Linear Quantization-Aware TrainingFindings of the Association for Computational LinguisticsWenzheng Zhang, Bingzheng Liu2026

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

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