Zechun Liu

According to our database, Zechun Liu authored at least 46 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

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

CoRR, 2024

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

CoRR, 2024

An Introduction to Vision-Language Modeling.

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

CoRR, 2024

SpinQuant: LLM quantization with learned rotations.

Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort

CoRR, 2024

MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases.

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

On the Open Prompt Challenge in Conditional Audio Generation.

Ernie Chang, Sidd Srinivasan, Mahi Luthra, Pin-Jie Lin, Varun Nagaraja, Forrest N. Iandola, Zechun Liu, Zhaoheng Ni, Changsheng Zhao, Yangyang Shi, Vikas Chandra

Proceedings of the IEEE International Conference on Acoustics, 2024

RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization.

Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Scaling Parameter-Constrained Language Models with Quality Data.

Ernie Chang, Matteo Paltenghi, Yang Li, Pin-Jie Lin, Changsheng Zhao, Patrick Huber, Zechun Liu, Rastislav Rabatin, Yangyang Shi, Vikas Chandra

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: EMNLP 2024, 2024

Target-Aware Language Modeling via Granular Data Sampling.

Ernie Chang, Pin-Jie Lin, Yang Li, Changsheng Zhao, Daeil Kim, Rastislav Rabatin, Zechun Liu, Yangyang Shi, Vikas Chandra

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

LLM-QAT: Data-Free Quantization Aware Training for Large Language Models.

Zechun Liu, Barlas Oguz, Changsheng Zhao, Ernie Chang, Pierre Stock, Yashar Mehdad, Yangyang Shi, Raghuraman Krishnamoorthi, Vikas Chandra

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts.

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

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning.

Jun Chen, Deyao Zhu, Xiaoqian Shen, Xiang Li, Zechun Liu, Pengchuan Zhang, Raghuraman Krishnamoorthi, Vikas Chandra, Yunyang Xiong, Mohamed Elhoseiny

CoRR, 2023

Efficient Quantization-aware Training with Adaptive Coreset Selection.

Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng

CoRR, 2023

EBSR: Enhanced Binary Neural Network for Image Super-Resolution.

Renjie Wei, Shuwen Zhang, Zechun Liu, Meng Li, Yuchen Fan, Runsheng Wang, Ru Huang

CoRR, 2023

Oscillation-free Quantization for Low-bit Vision Transformers.

Shih-Yang Liu, Zechun Liu, Kwang-Ting Cheng

Proceedings of the International Conference on Machine Learning, 2023

LLM-FP4: 4-Bit Floating-Point Quantized Transformers.

Shih-Yang Liu, Zechun Liu, Xijie Huang, Pingcheng Dong, Kwang-Ting Cheng

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Binary and Ternary Natural Language Generation.

Zechun Liu, Barlas Oguz, Aasish Pappu, Yangyang Shi, Raghuraman Krishnamoorthi

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Weight-Dependent Gates for Network Pruning.

Yun Li, Zechun Liu, Weiqun Wu, Haotian Yao, Xiangyu Zhang, Chi Zhang, Baoqun Yin

IEEE Trans. Circuits Syst. Video Technol., 2022

BiT: Robustly Binarized Multi-distilled Transformer.

Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, Meng Li, Raghuraman Krishnamoorthi, Yashar Mehdad

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

SDQ: Stochastic Differentiable Quantization with Mixed Precision.

Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric P. Xing, Kwang-Ting Cheng

Proceedings of the International Conference on Machine Learning, 2022

Sliced Recursive Transformer.

Zhiqiang Shen, Zechun Liu, Eric P. Xing

Proceedings of the Computer Vision, 2022

Data-Free Neural Architecture Search via Recursive Label Calibration.

Zechun Liu, Zhiqiang Shen, Yun Long, Eric P. Xing, Kwang-Ting Cheng, Chas Leichner

Proceedings of the Computer Vision, 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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Un-mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning.

Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell, Eric Poe Xing

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Stereo Neural Vernier Caliper.

Shichao Li, Zechun Liu, Zhiqiang Shen, Kwang-Ting Cheng

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Joint Multi-Dimension Pruning via Numerical Gradient Update.

Zechun Liu, Xiangyu Zhang, Zhiqiang Shen, Yichen Wei, Kwang-Ting Cheng, Jian Sun

IEEE Trans. Image Process., 2021

CDTD: A Large-Scale Cross-Domain Benchmark for Instance-Level Image-to-Image Translation and Domain Adaptive Object Detection.

Zhiqiang Shen, Mingyang Huang, Jianping Shi, Zechun Liu, Harsh Maheshwari, Yutong Zheng, Xiangyang Xue, Marios Savvides, Thomas S. Huang

Int. J. Comput. Vis., 2021

Conditional Link Prediction of Category-Implicit Keypoint Detection.

Ellen Yi-Ge, Rui Fan, Zechun Liu, Zhiqiang Shen

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

How Do Adam and Training Strategies Help BNNs Optimization.

Zechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng

Proceedings of the 38th International Conference on Machine Learning, 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

Proceedings of the 9th International Conference on Learning Representations, 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

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

"BNN - BN = ?": Training Binary Neural Networks Without Batch Normalization.

Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 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

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance.

Zechun Liu, Wenhan Luo, Baoyuan Wu, Xin Yang, Wei Liu, Kwang-Ting Cheng

Int. J. Comput. Vis., 2020

Joint Multi-Dimension Pruning.

Zechun Liu, Xiangyu Zhang, Zhiqiang Shen, Zhe Li, Yichen Wei, Kwang-Ting Cheng, Jian Sun

CoRR, 2020

Rethinking Image Mixture for Unsupervised Visual Representation Learning.

Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell

CoRR, 2020

Attentive Cutmix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification.

Devesh Walawalkar, Zhiqiang Shen, Zechun Liu, Marios Savvides

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functions.

Zechun Liu, Zhiqiang Shen, Marios Savvides, Kwang-Ting Cheng

Proceedings of the Computer Vision - ECCV 2020, 2020

Weight-Dependent Gates for Differentiable Neural Network Pruning.

Yun Li, Weiqun Wu, Zechun Liu, Chi Zhang, Xiangyu Zhang, Haotian Yao, Baoqun Yin

Proceedings of the Computer Vision - ECCV 2020 Workshops, 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

Proceedings of the Computer Vision - ECCV 2020, 2020

Binarizing MobileNet via Evolution-Based Searching.

Hai Phan, Zechun Liu, Dang Huynh, Marios Savvides, Kwang-Ting Cheng, Zhiqiang Shen

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization.

Koen Helwegen, James Widdicombe, Lukas Geiger, Zechun Liu, Kwang-Ting Cheng, Roeland Nusselder

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning.

Zechun Liu, Haoyuan Mu, Xiangyu Zhang, Zichao Guo, Xin Yang, Kwang-Ting Cheng, Jian Sun

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

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

Proceedings of the Computer Vision - ECCV 2018, 2018

2016

BDB: biopanning data bank.

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

Nucleic Acids Res., 2016