← Back to papers

2024 ICML ICML 2024

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Authors

Wei Huang , Yangdong Liu , Haotong Qin , Ying Li , Shiming Zhang , Xianglong Liu , Michele Magno , Xiaojuan Qi

Related papers

Learning Latent Dynamic Robust Representations for World Models 2024

Beyond Individual Input for Deep Anomaly Detection on Tabular Data 2024

Risk Estimation in a Markov Cost Process: Lower and Upper Bounds 2024

Collapse-Aware Triplet Decoupling for Adversarially Robust Image Retrieval 2024

Ranking-based Client Imitation Selection for Efficient Federated Learning 2024