🧑‍🔬 Who cites Xiaoxia Wu

207 citations of their works from 207 papers of our library (of the 149,439 whose bibliographies we read) · 23 with a page here, the most cited first · ← Xiaoxia Wu

1. QLoRA: Efficient Finetuning of Quantized LLMsConference on Neural Information Processing Systems (NeurIPS)Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, et al.2023 · 2,929 citations
2. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
3. LLM-Pruner: On the Structural Pruning of Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Xinyin Ma, Gongfan Fang, Xinchao Wang2023 · 452 citations
4. FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPUarXiv:2303.06865Ying Sheng, Lianmin Zheng, Binhang Yuan, et al.2023 · 402 citations
5. 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
6. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
7. LLM-QAT: Data-Free Quantization Aware Training for Large Language ModelsFindings of the Association for Computational LinguisticsZechun Liu, Barlas Oguz, Changsheng Zhao, et al.2024 · 276 citations
8. SqueezeLLM: Dense-and-Sparse QuantizationarXiv:2306.07629Sehoon Kim, Coleman Hooper, Amir Gholami, et al.2023 · 170 citations
9. Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative DecodingAnnual Meeting of the Association for Computational Linguistics (ACL)Jun Zhang, Jue Wang, Huan Li, et al.2024 · 148 citations
10. The case for 4-bit precision: k-bit Inference Scaling LawsarXiv:2212.09720Tim Dettmers, Luke Zettlemoyer2022 · 123 citations
11. A Survey of Small Language ModelsarXiv:2410.20011Chien Van Nguyen, Xuan Shen, Ryan Aponte, et al.2024 · 31 citations
12. What is the Role of Small Models in the LLM Era: A SurveyComputational LinguisticsLihu Chen, Gael Varoquaux2024 · 23 citations
13. Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zihan Qiu, Zeyu Huang, Bo Zheng, et al.2025 · 21 citations
14. “Give Me BF16 or Give Me Death”? Accuracy-Performance Trade-Offs in LLM QuantizationAnnual Meeting of the Association for Computational Linguistics (ACL)Eldar Kurtic, Alexandre Noll Marques, Shubhra Pandit, et al.2025 · 21 citations
15. TigerBot: An Open Multilingual Multitask LLMarXiv:2312.08688Ye Chen, Wei Cai, Liangmin Wu, et al.2023 · 15 citations
16. Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUsarXiv:2505.04519Yehui Tang, Yichun Yin, Yaoyuan Wang, et al.2025 · 8 citations
17. KNN-SSD: Enabling Dynamic Self-Speculative Decoding via Nearest Neighbor Layer Set OptimizationFindings of the Association for Computational LinguisticsMingbo Song, Heming Xia, Jun Zhang, et al.2026 · 5 citations
18. Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion ScalearXiv:2603.25040Yicheng Zou, Dongsheng Zhu, Lin Zhu, et al.2026 · 3 citations
19. Beyond Variance: Knowledge-Aware LLM Compression via Fisher-Aligned Subspace DiagnosticsAnnual Meeting of the Association for Computational Linguistics (ACL)Ibne Farabi Shihab, Sanjeda Akter, Anuj Sharma2026 · 1 citation
20. DELTA: Dynamic Layer-Aware Token Attention for Efficient Long-Context ReasoningFindings of the Association for Computational LinguisticsHossein Entezari Zarch, Lei Gao, Chaoyi Jiang, et al.2026 · 1 citation
21. Are Large Language Models Economically Viable for Industry Deployment?Annual Meeting of the Association for Computational Linguistics (ACL)Abdullah Mohammad, Sushant Kumar Ray, Pushkar Arora, et al.2026
22. Embracing Anisotropy: Turning Massive Activations into Interpretable Control Knobs for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Youngji Roh, Hyunjin Cho, Jaehyung Kim2026
23. Quantizing Whisper: How Design Choices Affect ASR PerformanceSpeech Language Models in Low-Resource Settings: Performance, Evaluation, and Bias Analysis (SPEAKABLE) @ LRECArthur Söhler, Julian Irigoyen, Andreas Søeborg Kirkedal2026

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