Who cites Haoli Bai
- LLM-Pruner: On the Structural Pruning of Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Xinyin Ma, Gongfan Fang, Xinchao Wang2023 · 452 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 · 304 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 · 296 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 · 276 citations
- SqueezeLLM: Dense-and-Sparse QuantizationarXiv:2306.07629Sehoon Kim, Coleman Hooper, Amir Gholami, et al.2023 · 170 citations
- Efficient 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 citations
- I-BERT: Integer-only BERT QuantizationInternational Conference on Machine Learning (ICML)Sehoon Kim, Amir Gholami, Zhewei Yao, et al.2021 · 122 citations
- MoEfication: Transformer Feed-forward Layers are Mixtures of ExpertsFindings of the Association for Computational LinguisticsZhengyan Zhang, Yankai Lin, Zhiyuan Liu, et al.2022 · 115 citations
- Retrieval-Augmented Generation for Natural Language Processing: A SurveyArtificial Intelligence ReviewShangyu Wu, Ying Xiong, Yufei Cui, et al.2024 · 86 citations
- 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
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