Liu, Zechun

31 publications

ICML 2025 Agent-as-a-Judge: Evaluate Agents with Agents Mingchen Zhuge, Changsheng Zhao, Dylan R. Ashley, Wenyi Wang, Dmitrii Khizbullin, Yunyang Xiong, Zechun Liu, Ernie Chang, Raghuraman Krishnamoorthi, Yuandong Tian, Yangyang Shi, Vikas Chandra, Jürgen Schmidhuber

ICCV 2025 Efficient Track Anything Yunyang Xiong, Chong Zhou, Xiaoyu Xiang, Lemeng Wu, Chenchen Zhu, Zechun Liu, Saksham Suri, Balakrishnan Varadarajan, Ramya Akula, Forrest Iandola, Raghuraman Krishnamoorthi, Bilge Soran, Vikas Chandra

ICML 2025 LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding Xiaoqian Shen, Yunyang Xiong, Changsheng Zhao, Lemeng Wu, Jun Chen, Chenchen Zhu, Zechun Liu, Fanyi Xiao, Balakrishnan Varadarajan, Florian Bordes, Zhuang Liu, Hu Xu, Hyunwoo J. Kim, Bilge Soran, Raghuraman Krishnamoorthi, Mohamed Elhoseiny, Vikas Chandra

ICML 2025 PARQ: Piecewise-Affine Regularized Quantization Lisa Jin, Jianhao Ma, Zechun Liu, Andrey Gromov, Aaron Defazio, Lin Xiao

ICLR 2025 Param$\Delta$ for Direct Mixing: Post-Train Large Language Model at Zero Cost Sheng Cao, Mingrui Wu, Karthik Prasad, Yuandong Tian, Zechun Liu

NeurIPS 2025 ParetoQ: Improving Scaling Laws in Extremely Low-Bit LLM Quantization Zechun Liu, Changsheng Zhao, Hanxian Huang, Sijia Chen, Jing Zhang, Jiawei Zhao, Scott Roy, Lisa Jin, Yunyang Xiong, Yangyang Shi, Lin Xiao, Yuandong Tian, Bilge Soran, Raghuraman Krishnamoorthi, Tijmen Blankevoort, Vikas Chandra

ICLR 2025 R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference Zhenyu Zhang, Zechun Liu, Yuandong Tian, Harshit Khaitan, Zhangyang Wang, Steven Li

NeurIPS 2025 RDD: Retrieval-Based Demonstration Decomposer for Planner Alignment in Long-Horizon Tasks Mingxuan Yan, Yuping Wang, Zechun Liu, Jiachen Li

ICLR 2025 SpinQuant: LLM Quantization with Learned Rotations Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort

ICML 2024 MobileLLM: Optimizing Sub-Billion Parameter Language Models for On-Device Use Cases Zechun Liu, Changsheng Zhao, Forrest Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra

TMLR 2024 Robust and Efficient Quantization-Aware Training via Coreset Selection Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng

ICML 2023 Oscillation-Free Quantization for Low-Bit Vision Transformers Shih-Yang Liu, Zechun Liu, Kwang-Ting Cheng

NeurIPS 2022 BiT: Robustly Binarized Multi-Distilled Transformer Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, Meng Li, Raghuraman Krishnamoorthi, Yashar Mehdad

ECCV 2022 Data-Free Neural Architecture Search via Recursive Label Calibration Zechun Liu, Zhiqiang Shen, Yun Long, Eric Xing, Kwang-Ting Cheng, Chas Leichner

CVPR 2022 Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric P. Xing, Zhiqiang Shen

ICML 2022 SDQ: Stochastic Differentiable Quantization with Mixed Precision Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Hu Xianghong, Jeffry Wicaksana, Eric Xing, Kwang-Ting Cheng

ECCV 2022 Sliced Recursive Transformer Zhiqiang Shen, Zechun Liu, Eric Xing

AAAI 2022 Stereo Neural Vernier Caliper Shichao Li, Zechun Liu, Zhiqiang Shen, Kwang-Ting Cheng

AAAI 2022 Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell, Eric Poe Xing

CVPR 2022 Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing

CVPRW 2021 "BNN - BN = ?": Training Binary Neural Networks Without Batch Normalization Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang

WACV 2021 Conditional Link Prediction of Category-Implicit Keypoint Detection Ellen Yi-Ge, Rui Fan, Zechun Liu, Zhiqiang Shen

ICML 2021 How Do Adam and Training Strategies Help BNNs Optimization Zechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng

ICLR 2021 Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study Zhiqiang Shen, Zechun Liu, Dejia Xu, Zitian Chen, Kwang-Ting Cheng, Marios Savvides

AAAI 2021 Partial Is Better than All: Revisiting Fine-Tuning Strategy for Few-Shot Learning Zhiqiang Shen, Zechun Liu, Jie Qin, Marios Savvides, Kwang-Ting Cheng

CVPR 2021 S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-Bit Neural Networks via Guided Distribution Calibration Zhiqiang Shen, Zechun Liu, Jie Qin, Lei Huang, Kwang-Ting Cheng, Marios Savvides

ECCV 2020 ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functions Zechun Liu, Zhiqiang Shen, Marios Savvides, Kwang-Ting Cheng

ECCV 2020 Single Path One-Shot Neural Architecture Search with Uniform Sampling Zichao Guo, Xiangyu Zhang, Haoyuan Mu, Wen Heng, Zechun Liu, Yichen Wei, Jian Sun

ECCVW 2020 Weight-Dependent Gates for Differentiable Neural Network Pruning Yun Li, Weiqun Wu, Zechun Liu, Chi Zhang, Xiangyu Zhang, Haotian Yao, Baoqun Yin

NeurIPS 2019 Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization Koen Helwegen, James Widdicombe, Lukas Geiger, Zechun Liu, Kwang-Ting Cheng, Roeland Nusselder

ECCV 2018 Bi-Real Net: Enhancing the Performance of 1-Bit CNNs with Improved Representational Capability and Advanced Training Algorithm Zechun Liu, Baoyuan Wu, Wenhan Luo, Xin Yang, Wei Liu, Kwang-Ting Cheng