Zechun Liu

99 papers A* 23A 2Misc 2Journal 60Unranked 12
YearRankTypeTitle / Venue / Authors
2026 J jnl
MobileLLM-Flash: Latency-Guided On-Device LLM Design for Industry Scale Deployment.
CoRR
Hanxian Huang, Igor Fedorov, Andrey Gromov, Bernard Beckerman, Naveen Suda, David Eriksson, Maximilian Balandat, Rylan Conway, Patrick Huber, Chinnadhurai Sankar, Ayushi Dalmia, Zechun Liu, Lemeng Wu, Tarek Elgamal, Adithya Sagar, Vikas Chandra, Raghuraman Krishnamoorthi
2026 J jnl
STEM: Scaling Transformers with Embedding Modules.
CoRR
Ranajoy Sadhukhan, Sheng Cao, Harry Dong, Changsheng Zhao, Attiano Purpura-Pontoniere, Yuandong Tian, Zechun Liu, Beidi Chen
2026 J jnl
VideoAuto-R1: Video Auto Reasoning via Thinking Once, Answering Twice.
CoRR
Shuming Liu, Mingchen Zhuge, Changsheng Zhao, Jun Chen, Lemeng Wu, Zechun Liu, Chenchen Zhu, Zhipeng Cai, Chong Zhou, Haozhe Liu, Ernie Chang, Saksham Suri, Hongyu Xu, Qi Qian, Wei Wen, Balakrishnan Varadarajan, Zhuang Liu, Hu Xu, Florian Bordes, Raghuraman Krishnamoorthi, Bernard Ghanem, Vikas Chandra, Yunyang Xiong
2026 J jnl
dTRPO: Trajectory Reduction in Policy Optimization of Diffusion Large Language Models.
CoRR
Wenxuan Zhang, Lemeng Wu, Changsheng Zhao, Ernie Chang, Mingchen Zhuge, Zechun Liu, Andy Su, Hanxian Huang, Jun Chen, Chong Zhou, Raghuraman Krishnamoorthi, Vikas Chandra, Mohamed Elhoseiny, Wei Wen
2025 A* conf
Agent-as-a-Judge: Evaluate Agents with Agents.
ICML
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
2025 A* conf
LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding.
ICML
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
2025 J jnl
MobileLLM-R1: Exploring the Limits of Sub-Billion Language Model Reasoners with Open Training Recipes.
CoRR
Changsheng Zhao, Ernie Chang, Zechun Liu, Chia-Jung Chang, Wei Wen, Chen Lai, Sheng Cao, Yuandong Tian, Raghuraman Krishnamoorthi, Yangyang Shi, Vikas Chandra
2025 A* conf
PARQ: Piecewise-Affine Regularized Quantization.
ICML
Lisa Jin, Jianhao Ma, Zechun Liu, Andrey Gromov, Aaron Defazio, Lin Xiao
2025 J jnl
PARQ: Piecewise-Affine Regularized Quantization.
CoRR
Lisa Jin, Jianhao Ma, Zechun Liu, Andrey Gromov, Aaron Defazio, Lin Xiao
2025 A* conf
ParamΔ for Direct Mixing: Post-Train Large Language Model At Zero Cost.
ICLR
Sheng Cao, Mingrui Wu, Karthik Prasad, Yuandong Tian, Zechun Liu
2025 J jnl
ParamΔ for Direct Weight Mixing: Post-Train Large Language Model at Zero Cost.
CoRR
Sheng Cao, Mingrui Wu, Karthik Prasad, Yuandong Tian, Zechun Liu
2025 J jnl
ParetoQ: Scaling Laws in Extremely Low-bit LLM Quantization.
CoRR
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
2025 A* conf
R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference.
ICLR
Zhenyu Zhang, Zechun Liu, Yuandong Tian, Harshit Khaitan, Zhangyang Wang, Steven Li
2025 J jnl
R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference.
CoRR
Zhenyu Zhang, Zechun Liu, Yuandong Tian, Harshit Khaitan, Zhangyang Wang, Steven Li
2025 J jnl
RDD: Retrieval-Based Demonstration Decomposer for Planner Alignment in Long-Horizon Tasks.
CoRR
Mingxuan Yan, Yuping Wang, Zechun Liu, Jiachen Li
2025 A conf
SCALES: Boost Binary Neural Network for Image Super-Resolution with Efficient Scalings.
DATE
Renjie Wei, Zechun Liu, Yuchen Fan, Runsheng Wang, Ru Huang, Meng Li
2025 A* conf
SpinQuant: LLM Quantization with Learned Rotations.
ICLR
Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort
2025 J jnl
The Path Not Taken: RLVR Provably Learns Off the Principals.
CoRR
Hanqing Zhu, Zhenyu Zhang, Hanxian Huang, DiJia Su, Zechun Liu, Jiawei Zhao, Igor Fedorov, Hamed Pirsiavash, Zhizhou Sha, Jinwon Lee, David Z. Pan, Zhangyang Wang, Yuandong Tian, Kai Sheng Tai
2024 J jnl
Agent-as-a-Judge: Evaluate Agents with Agents.
CoRR
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
2024 J jnl
An Introduction to Vision-Language Modeling.
CoRR
Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe, Vasu Sharma, Hu Xu, Xiaoqing Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari Hemmat, Jun Chen, Kushal Tirumala, Rim Assouel, Mazda Moayeri, Arjang Talattof, Kamalika Chaudhuri, Zechun Liu, Xilun Chen, Quentin Garrido, Karen Ullrich, Aishwarya Agrawal, Kate Saenko, Asli Celikyilmaz, Vikas Chandra
2024 J jnl
Efficient Track Anything.
CoRR
Yunyang Xiong, Chong Zhou, Xiaoyu Xiang, Lemeng Wu, Chenchen Zhu, Zechun Liu, Saksham Suri, Balakrishnan Varadarajan, Ramya Akula, Forrest N. Iandola, Raghuraman Krishnamoorthi, Bilge Soran, Vikas Chandra
2024 — conf
LLM-QAT: Data-Free Quantization Aware Training for Large Language Models.
ACL (Findings)
Zechun Liu, Barlas Oguz, Changsheng Zhao, Ernie Chang, Pierre Stock, Yashar Mehdad, Yangyang Shi, Raghuraman Krishnamoorthi, Vikas Chandra
2024 J jnl
Llama Guard 3-1B-INT4: Compact and Efficient Safeguard for Human-AI Conversations.
CoRR
Igor Fedorov, Kate Plawiak, Lemeng Wu, Tarek Elgamal, Naveen Suda, Eric Smith, Hongyuan Zhan, Jianfeng Chi, Yuriy Hulovatyy, Kimish Patel, Zechun Liu, Changsheng Zhao, Yangyang Shi, Tijmen Blankevoort, Mahesh Pasupuleti, Bilge Soran, Zacharie Delpierre Coudert, Rachad Alao, Raghuraman Krishnamoorthi, Vikas Chandra
2024 J jnl
LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding.
CoRR
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
2024 — conf
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts.
ACL (Findings)
Ganesh Jawahar, Haichuan Yang, Yunyang Xiong, Zechun Liu, Dilin Wang, Fei Sun, Meng Li, Aasish Pappu, Barlas Oguz, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Raghuraman Krishnamoorthi, Vikas Chandra
2024 A* conf
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases.
ICML
Zechun Liu, Changsheng Zhao, Forrest N. Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra
2024 J jnl
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases.
CoRR
Zechun Liu, Changsheng Zhao, Forrest N. Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra
2024 Misc conf
On the Open Prompt Challenge in Conditional Audio Generation.
ICASSP
Ernie Chang, Sidd Srinivasan, Mahi Luthra, Pin-Jie Lin, Varun Nagaraja, Forrest N. Iandola, Zechun Liu, Zhaoheng Ni, Changsheng Zhao, Yangyang Shi, Vikas Chandra
2024 — conf
RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization.
EMNLP (Findings)
Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng
2024 J jnl
RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization.
CoRR
Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng
2024 J jnl
Robust and Efficient Quantization-aware Training via Coreset Selection.
Trans. Mach. Learn. Res.
Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng
2024 — conf
Scaling Parameter-Constrained Language Models with Quality Data.
EMNLP (Industry Track)
Ernie Chang, Matteo Paltenghi, Yang Li, Pin-Jie Lin, Changsheng Zhao, Patrick Huber, Zechun Liu, Rastislav Rabatin, Yangyang Shi, Vikas Chandra
2024 J jnl
Scaling Parameter-Constrained Language Models with Quality Data.
CoRR
Ernie Chang, Matteo Paltenghi, Yang Li, Pin-Jie Lin, Changsheng Zhao, Patrick Huber, Zechun Liu, Rastislav Rabatin, Yangyang Shi, Vikas Chandra
2024 J jnl
SpinQuant: LLM quantization with learned rotations.
CoRR
Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort
2024 A* conf
Target-Aware Language Modeling via Granular Data Sampling.
EMNLP
Ernie Chang, Pin-Jie Lin, Yang Li, Changsheng Zhao, Daeil Kim, Rastislav Rabatin, Zechun Liu, Yangyang Shi, Vikas Chandra
2024 J jnl
Target-Aware Language Modeling via Granular Data Sampling.
CoRR
Ernie Chang, Pin-Jie Lin, Yang Li, Changsheng Zhao, Daeil Kim, Rastislav Rabatin, Zechun Liu, Yangyang Shi, Vikas Chandra
2023 — conf
Binary and Ternary Natural Language Generation.
ACL (1)
Zechun Liu, Barlas Oguz, Aasish Pappu, Yangyang Shi, Raghuraman Krishnamoorthi
2023 J jnl
Binary and Ternary Natural Language Generation.
CoRR
Zechun Liu, Barlas Oguz, Aasish Pappu, Yangyang Shi, Raghuraman Krishnamoorthi
2023 J jnl
EBSR: Enhanced Binary Neural Network for Image Super-Resolution.
CoRR
Renjie Wei, Shuwen Zhang, Zechun Liu, Meng Li, Yuchen Fan, Runsheng Wang, Ru Huang
2023 J jnl
Efficient Quantization-aware Training with Adaptive Coreset Selection.
CoRR
Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng
2023 A* conf
LLM-FP4: 4-Bit Floating-Point Quantized Transformers.
EMNLP
Shih-Yang Liu, Zechun Liu, Xijie Huang, Pingcheng Dong, Kwang-Ting Cheng
2023 J jnl
LLM-FP4: 4-Bit Floating-Point Quantized Transformers.
CoRR
Shih-Yang Liu, Zechun Liu, Xijie Huang, Pingcheng Dong, Kwang-Ting Cheng
2023 J jnl
LLM-QAT: Data-Free Quantization Aware Training for Large Language Models.
CoRR
Zechun Liu, Barlas Oguz, Changsheng Zhao, Ernie Chang, Pierre Stock, Yashar Mehdad, Yangyang Shi, Raghuraman Krishnamoorthi, Vikas Chandra
2023 J jnl
MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning.
CoRR
Jun Chen, Deyao Zhu, Xiaoqian Shen, Xiang Li, Zechun Liu, Pengchuan Zhang, Raghuraman Krishnamoorthi, Vikas Chandra, Yunyang Xiong, Mohamed Elhoseiny
2023 J jnl
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts.
CoRR
Ganesh Jawahar, Haichuan Yang, Yunyang Xiong, Zechun Liu, Dilin Wang, Fei Sun, Meng Li, Aasish Pappu, Barlas Oguz, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Raghuraman Krishnamoorthi, Vikas Chandra
2023 J jnl
On The Open Prompt Challenge In Conditional Audio Generation.
CoRR
Ernie Chang, Sidd Srinivasan, Mahi Luthra, Pin-Jie Lin, Varun Nagaraja, Forrest N. Iandola, Zechun Liu, Zhaoheng Ni, Changsheng Zhao, Yangyang Shi, Vikas Chandra
2023 A* conf
Oscillation-free Quantization for Low-bit Vision Transformers.
ICML
Shih-Yang Liu, Zechun Liu, Kwang-Ting Cheng
2023 J jnl
Oscillation-free Quantization for Low-bit Vision Transformers.
CoRR
Shih-Yang Liu, Zechun Liu, Kwang-Ting Cheng
2022 A* conf
BiT: Robustly Binarized Multi-distilled Transformer.
NeurIPS
Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, Meng Li, Raghuraman Krishnamoorthi, Yashar Mehdad
2022 J jnl
BiT: Robustly Binarized Multi-distilled Transformer.
CoRR
Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, Meng Li, Raghuraman Krishnamoorthi, Yashar Mehdad
2022 — conf
Data-Free Neural Architecture Search via Recursive Label Calibration.
ECCV (24)
Zechun Liu, Zhiqiang Shen, Yun Long, Eric P. Xing, Kwang-Ting Cheng, Chas Leichner
2022 A* conf
Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation.
CVPR
Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric P. Xing, Zhiqiang Shen
2022 A* conf
SDQ: Stochastic Differentiable Quantization with Mixed Precision.
ICML
Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric P. Xing, Kwang-Ting Cheng
2022 J jnl
SDQ: Stochastic Differentiable Quantization with Mixed Precision.
CoRR
Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric P. Xing, Kwang-Ting Cheng
2022 — conf
Sliced Recursive Transformer.
ECCV (24)
Zhiqiang Shen, Zechun Liu, Eric P. Xing
2022 A* conf
Stereo Neural Vernier Caliper.
AAAI
Shichao Li, Zechun Liu, Zhiqiang Shen, Kwang-Ting Cheng
2022 J jnl
Stereo Neural Vernier Caliper.
CoRR
Shichao Li, Zechun Liu, Zhiqiang Shen, Kwang-Ting Cheng
2022 A* conf
Un-mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning.
AAAI
Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell, Eric Poe Xing
2022 A* conf
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space.
CVPR
Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing
2022 J jnl
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space.
CoRR
Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing
2022 J jnl
Weight-Dependent Gates for Network Pruning.
IEEE Trans. Circuits Syst. Video Technol.
Yun Li, Zechun Liu, Weiqun Wu, Haotian Yao, Xiangyu Zhang, Chi Zhang, Baoqun Yin
2021 — conf
"BNN - BN = ?": Training Binary Neural Networks Without Batch Normalization.
CVPR Workshops
Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang
2021 J jnl
"BNN - BN = ?": Training Binary Neural Networks without Batch Normalization.
CoRR
Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang
2021 J jnl
CDTD: A Large-Scale Cross-Domain Benchmark for Instance-Level Image-to-Image Translation and Domain Adaptive Object Detection.
Int. J. Comput. Vis.
Zhiqiang Shen, Mingyang Huang, Jianping Shi, Zechun Liu, Harsh Maheshwari, Yutong Zheng, Xiangyang Xue, Marios Savvides, Thomas S. Huang
2021 A conf
Conditional Link Prediction of Category-Implicit Keypoint Detection.
WACV
Ellen Yi-Ge, Rui Fan, Zechun Liu, Zhiqiang Shen
2021 J jnl
Data-Free Neural Architecture Search via Recursive Label Calibration.
CoRR
Zechun Liu, Zhiqiang Shen, Yun Long, Eric P. Xing, Kwang-Ting Cheng, Chas Leichner
2021 A* conf
How Do Adam and Training Strategies Help BNNs Optimization.
ICML
Zechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng
2021 J jnl
How Do Adam and Training Strategies Help BNNs Optimization?
CoRR
Zechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng
2021 A* conf
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study.
ICLR
Zhiqiang Shen, Zechun Liu, Dejia Xu, Zitian Chen, Kwang-Ting Cheng, Marios Savvides
2021 J jnl
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study.
CoRR
Zhiqiang Shen, Zechun Liu, Dejia Xu, Zitian Chen, Kwang-Ting Cheng, Marios Savvides
2021 J jnl
Joint Multi-Dimension Pruning via Numerical Gradient Update.
IEEE Trans. Image Process.
Zechun Liu, Xiangyu Zhang, Zhiqiang Shen, Yichen Wei, Kwang-Ting Cheng, Jian Sun
2021 J jnl
Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation.
CoRR
Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric P. Xing, Zhiqiang Shen
2021 A* conf
Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning.
AAAI
Zhiqiang Shen, Zechun Liu, Jie Qin, Marios Savvides, Kwang-Ting Cheng
2021 J jnl
Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning.
CoRR
Zhiqiang Shen, Zechun Liu, Jie Qin, Marios Savvides, Kwang-Ting Cheng
2021 A* conf
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-Bit Neural Networks via Guided Distribution Calibration.
CVPR
Zhiqiang Shen, Zechun Liu, Jie Qin, Lei Huang, Kwang-Ting Cheng, Marios Savvides
2021 J jnl
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration.
CoRR
Zhiqiang Shen, Zechun Liu, Jie Qin, Lei Huang, Kwang-Ting Cheng, Marios Savvides
2021 J jnl
Sliced Recursive Transformer.
CoRR
Zhiqiang Shen, Zechun Liu, Eric P. Xing
2020 J jnl
Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification.
CoRR
Devesh Walawalkar, Zhiqiang Shen, Zechun Liu, Marios Savvides
2020 Misc conf
Attentive Cutmix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification.
ICASSP
Devesh Walawalkar, Zhiqiang Shen, Zechun Liu, Marios Savvides
2020 J jnl
Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance.
Int. J. Comput. Vis.
Zechun Liu, Wenhan Luo, Baoyuan Wu, Xin Yang, Wei Liu, Kwang-Ting Cheng
2020 A* conf
Binarizing MobileNet via Evolution-Based Searching.
CVPR
Hai Phan, Zechun Liu, Dang Huynh, Marios Savvides, Kwang-Ting Cheng, Zhiqiang Shen
2020 J jnl
Binarizing MobileNet via Evolution-based Searching.
CoRR
Hai Phan, Zechun Liu, Dang Huynh, Marios Savvides, Kwang-Ting Cheng, Zhiqiang Shen
2020 J jnl
Conditional Link Prediction of Category-Implicit Keypoint Detection.
CoRR
Ellen Yi-Ge, Rui Fan, Zechun Liu, Zhiqiang Shen
2020 J jnl
Joint Multi-Dimension Pruning.
CoRR
Zechun Liu, Xiangyu Zhang, Zhiqiang Shen, Zhe Li, Yichen Wei, Kwang-Ting Cheng, Jian Sun
2020 — conf
ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functions.
ECCV (14)
Zechun Liu, Zhiqiang Shen, Marios Savvides, Kwang-Ting Cheng
2020 J jnl
ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functions.
CoRR
Zechun Liu, Zhiqiang Shen, Marios Savvides, Kwang-Ting Cheng
2020 J jnl
Rethinking Image Mixture for Unsupervised Visual Representation Learning.
CoRR
Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell
2020 — conf
Single Path One-Shot Neural Architecture Search with Uniform Sampling.
ECCV (16)
Zichao Guo, Xiangyu Zhang, Haoyuan Mu, Wen Heng, Zechun Liu, Yichen Wei, Jian Sun
2020 — conf
Weight-Dependent Gates for Differentiable Neural Network Pruning.
ECCV Workshops (5)
Yun Li, Weiqun Wu, Zechun Liu, Chi Zhang, Xiangyu Zhang, Haotian Yao, Baoqun Yin
2020 J jnl
Weight-dependent Gates for Network Pruning.
CoRR
Yun Li, Weiqun Wu, Zechun Liu, Chi Zhang, Xiangyu Zhang, Haotian Yao, Baoqun Yin
2019 A* conf
Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization.
NeurIPS
Koen Helwegen, James Widdicombe, Lukas Geiger, Zechun Liu, Kwang-Ting Cheng, Roeland Nusselder
2019 J jnl
Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization.
CoRR
Koen Helwegen, James Widdicombe, Lukas Geiger, Zechun Liu, Kwang-Ting Cheng, Roeland Nusselder
2019 A* conf
MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning.
ICCV
Zechun Liu, Haoyuan Mu, Xiangyu Zhang, Zichao Guo, Xin Yang, Kwang-Ting Cheng, Jian Sun
2019 J jnl
MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning.
CoRR
Zechun Liu, Haoyuan Mu, Xiangyu Zhang, Zichao Guo, Xin Yang, Kwang-Ting (Tim) Cheng, Jian Sun
2019 J jnl
Single Path One-Shot Neural Architecture Search with Uniform Sampling.
CoRR
Zichao Guo, Xiangyu Zhang, Haoyuan Mu, Wen Heng, Zechun Liu, Yichen Wei, Jian Sun
2018 J jnl
Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance.
CoRR
Zechun Liu, Wenhan Luo, Baoyuan Wu, Xin Yang, Wei Liu, Kwang-Ting Cheng
2018 — conf
Bi-Real Net: Enhancing the Performance of 1-Bit CNNs with Improved Representational Capability and Advanced Training Algorithm.
ECCV (15)
Zechun Liu, Baoyuan Wu, Wenhan Luo, Xin Yang, Wei Liu, Kwang-Ting Cheng
2018 J jnl
Bi-Real Net: Enhancing the Performance of 1-bit CNNs With Improved Representational Capability and Advanced Training Algorithm.
CoRR
Zechun Liu, Baoyuan Wu, Wenhan Luo, Xin Yang, Wei Liu, Kwang-Ting Cheng
2016 J jnl
BDB: biopanning data bank.
Nucleic Acids Res.
Bifang He, Guoshi Chai, Yaocong Duan, Zhiqiang Yan, Liuyang Qiu, Huixiong Zhang, Zechun Liu, Qiang He, Ke Han, Beibei Ru, Feng-Biao Guo, Hui Ding, Hao Lin, Xianlong Wang, Nini Rao, Peng Zhou, Jian Huang