🧑‍🔬 Who cites Zhaoyang Zhang

193 citations of their works from 193 papers of our library (of the 149,439 whose bibliographies we read) · 32 with a page here, the most cited first · ← Zhaoyang Zhang

1. A Survey on Model Compression for Large Language ModelsTransactions of the Association for Computational Linguistics (TACL)Xunyu Zhu, Jian Li, Yong Liu, et al.2024 · 381 citations
2. KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache QuantizationConference on Neural Information Processing Systems (NeurIPS)Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh, et al.2024 · 294 citations
3. QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMsConference on Neural Information Processing Systems (NeurIPS)Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, et al.2024 · 254 citations
4. LLM in a flash: Efficient Large Language Model Inference with Limited MemoryAnnual Meeting of the Association for Computational Linguistics (ACL)Keivan Alizadeh, Seyed Iman Mirzadeh, Dmitry Belenko, et al.2024 · 193 citations
5. SqueezeLLM: Dense-and-Sparse QuantizationarXiv:2306.07629Sehoon Kim, Coleman Hooper, Amir Gholami, et al.2023 · 170 citations
6. Atom: Low-bit Quantization for Efficient and Accurate LLM ServingMLSys 2024Yilong Zhao, Chien-Yu Lin, Kan Zhu, et al.2023 · 156 citations
7. QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM ServingMLSys 2025Yujun Lin, Haotian Tang, Shang Yang, et al.2024 · 120 citations
8. QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice CodebooksarXiv:2402.04396Albert Tseng, Jerry Chee, Qingyao Sun, et al.2024 · 117 citations
9. A Survey on Efficient Inference for Large Language ModelsarXiv:2404.14294Zixuan Zhou, Xuefei Ning, Ke Hong, et al.2024 · 113 citations
10. 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
11. A Survey of Resource-efficient LLM and Multimodal Foundation ModelsarXiv:2401.08092Mengwei Xu, Wangsong Yin, Dongqi Cai, et al.2024 · 54 citations
12. A Survey of On-Policy Distillation for Large Language ModelsarXiv:2604.00626Mingyang Song, Mao Zheng2026 · 41 citations
13. Self-Distilled RLVRarXiv:2604.03128Chenxu Yang, Chuanyu Qin, Qingyi Si, et al.2026 · 37 citations
14. A Survey of Small Language ModelsarXiv:2410.20011Chien Van Nguyen, Xuan Shen, Ryan Aponte, et al.2024 · 31 citations
15. L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hyesung Jeon, Yulhwa Kim, Jae-Joon Kim2025 · 15 citations
16. Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy DistillationarXiv:2604.13010Yecheng Wu, Song Han, Han Cai2026 · 10 citations
17. HDPO: Hybrid Distillation Policy Optimization via Privileged Self-DistillationarXiv:2603.23871Ken Ding2026 · 8 citations
18. Exploring Layer-wise Information Effectiveness for Post-Training Quantization in Small Language ModelsFindings of the Association for Computational LinguisticsHe Xiao, Qingyao Yang, Dirui Xie, et al.2026 · 5 citations
19. Self-Distilled Policy GradientarXiv:2606.04036Yifeng Liu, Shiyuan Zhang, Yifan Zhang, et al.2026 · 5 citations
20. Bit-by-Bit: Progressive QAT Strategy with Outlier Channel Splitting for Stable Low-Bit LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Binxing Xu, Hao Gu, Lujun Li, et al.2026 · 3 citations
21. SharVeT: Similarity-aware Parameter Sharing with Vector-based Tuning for Efficient LLM CompressionAnnual Meeting of the Association for Computational Linguistics (ACL)Jeongin Yun, Jaeri Lee, Jongjin Kim, et al.2026 · 1 citation
22. Unleashing Low-Bit Inference on Ascend NPUs: A Comprehensive Evaluation of HiFloat FormatsAnnual Meeting of the Association for Computational Linguistics (ACL)Pengxiang Zhao, Hui-Ling Zhen, Xing Li, et al.2026 · 1 citation
23. ACBQ: Adaptive Cross-Block Quantization of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hailing Wang, Jianglin Lu, Yitian Zhang, et al.2026
24. ArcLight: A Lightweight LLM Inference Architecture for Many-Core CPUsAnnual Meeting of the Association for Computational Linguistics (ACL)Yuzhuang Xu, Xu Han, Yuxuan Li, et al.2026
25. 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
26. BWLA: Breaking the Barrier of W1AX Post-Training Quantization for LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhixiong Zhao, Zukang Xu, Dawei Yang2026
27. EfficientLLM: Unified Pruning-Aware Pretraining for Auto-Designed Compact Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xingrun Xing, Zheng Liu, Shitao Xiao, et al.2026
28. FAQ: Mitigating Quantization Error via Regenerating Calibration Data with Family-Aware QuantizationFindings of the Association for Computational LinguisticsHaiyang Xiao, Weiqing Li, Jinyue Guo, et al.2026
29. Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Cuong Pham, Anh Dung Hoang, Cuong C. Nguyen, et al.2026
30. PE-QAT: Parameter-Efficient Quantization-Aware Training for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Shresth Mishra2026
31. pQuant: Towards Effective Low-Bit Language Models via Decoupled Linear Quantization-Aware TrainingFindings of the Association for Computational LinguisticsWenzheng Zhang, Bingzheng Liu2026
32. SCVQ: Sparse-Compensated Vector Quantization for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zixuan Zhou, Yujun Diao, Zicheng Kong, et al.2026

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