FBI-LLM: Scaling Up Fully Binarized LLMs from Scratch via Autoregressive Distillation

9 July 2024

Papers citing "FBI-LLM: Scaling Up Fully Binarized LLMs from Scratch via Autoregressive Distillation"

4 / 4 papers shown

Title
Membership Inference Risks in Quantized Models: A Theoretical and Empirical Study Eric Aubinais Philippe Formont Pablo Piantanida Elisabeth Gassiat 38 0 0 10 Feb 2025
OneBit: Towards Extremely Low-bit Large Language Models Yuzhuang Xu Xu Han Zonghan Yang Shuo Wang Qingfu Zhu Zhiyuan Liu Weidong Liu Wanxiang Che MQ 51 36 0 17 Feb 2024
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs Wei Huang Yangdong Liu Haotong Qin Ying Li Shiming Zhang Xianglong Liu Michele Magno Xiaojuan Qi MQ 77 63 0 06 Feb 2024
Collaborative Multi-Teacher Knowledge Distillation for Learning Low Bit-width Deep Neural Networks Cuong Pham Tuan Hoang Thanh-Toan Do FedML MQ 16 13 0 27 Oct 2022