🔗 Who cites «TernaryBERT: Distillation-aware Ultra-low Bit BERT»

65 papers of our library cite it (of the 141,840 whose bibliographies we read) · 7 with a page here, the most cited first · ← back to «TernaryBERT: Distillation-aware Ultra-low Bit BERT»

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
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
1. SqueezeLLM: Dense-and-Sparse QuantizationarXiv:2306.07629Sehoon Kim, Coleman Hooper, Amir Gholami, et al.2023 · 168 citations
   BinaryBERT: Pushing the Limit of BERT QuantizationAnnual Meeting of the Association for Computational Linguistics (ACL)Haoli Bai, Wei Zhang, Lu Hou, et al.2021 · 165 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 · 120 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

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

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