Liu, Zichang

8 publications

ICML 2023 Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Re, Beidi Chen

ICLR 2023 Learning Multimodal Data Augmentation in Feature Space Zichang Liu, Zhiqiang Tang, Xingjian Shi, Aston Zhang, Mu Li, Anshumali Shrivastava, Andrew Gordon Wilson

NeurIPS 2023 One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning Zichang Liu, Zhaozhuo Xu, Benjamin Coleman, Anshumali Shrivastava

NeurIPS 2023 Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time Zichang Liu, Aditya Desai, Fangshuo Liao, Weitao Wang, Victor Xie, Zhaozhuo Xu, Anastasios Kyrillidis, Anshumali Shrivastava

NeurIPS 2022 Retaining Knowledge for Learning with Dynamic Definition Zichang Liu, Benjamin Coleman, Tianyi Zhang, Anshumali Shrivastava

CVPR 2022 SAR-Net: Shape Alignment and Recovery Network for Category-Level 6d Object Pose and Size Estimation Haitao Lin, Zichang Liu, Chilam Cheang, Yanwei Fu, Guodong Guo, Xiangyang Xue

ECML-PKDD 2021 Efficient and Less Centralized Federated Learning Li Chou, Zichang Liu, Zhuang Wang, Anshumali Shrivastava

ICLR 2021 MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan Lingjie Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Re