Who cites Lu Hou
- SqueezeLLM: Dense-and-Sparse QuantizationarXiv:2306.07629Sehoon Kim, Coleman Hooper, Amir Gholami, et al.2023 · 168 citationsBinaryBERT: Pushing the Limit of BERT QuantizationAnnual Meeting of the Association for Computational Linguistics (ACL)Haoli Bai, Wei Zhang, Lu Hou, et al.2021 · 165 citationsEfficient Methods for Natural Language Processing: A SurveyTransactions of the Association for Computational Linguistics (TACL)Marcos Treviso, Ji-Ung Lee, Tianchu Ji, et al.2023 · 145 citationsI-BERT: Integer-only BERT QuantizationInternational Conference on Machine Learning (ICML)Sehoon Kim, Amir Gholami, Zhewei Yao, et al.2021 · 120 citationsMoEfication: Transformer Feed-forward Layers are Mixtures of ExpertsFindings of the Association for Computational LinguisticsZhengyan Zhang, Yankai Lin, Zhiyuan Liu, et al.2022 · 115 citations
LLM-Pruner: On the Structural Pruning of Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Xinyin Ma, Gongfan Fang, Xinchao Wang2023 · 448 citations
ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale TransformersConference on Neural Information Processing Systems (NeurIPS)Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, et al.2022 · 302 citations
AdapterDrop: On the Efficiency of Adapters in TransformersConference on Empirical Methods in Natural Language Processing (EMNLP)Andreas Rücklé, Gregor Geigle, Max Glockner, et al.2021 · 295 citations
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 · 275 citations
This page in Markdown → https://md.research.elamur.ai/free/en/authors/lu-hou/cited-by/