Zechun Liu
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
39
Venues
11
Active years
2018–2026
Best venue rank
A*
Where they publish
Papers
39 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | MobileLLM-Flash: Latency-Guided On-Device LLM Design for Industry Scale Deployment. | 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 |
| 2025 | DATE | SCALES: Boost Binary Neural Network for Image Super-Resolution with Efficient Scalings. | Renjie Wei, Zechun Liu, Yuchen Fan, Runsheng Wang, Ru Huang, Meng Li |
| 2025 | ICCV | Efficient Track Anything. | 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 |
| 2025 | ICLR | R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference. | Zhenyu Zhang, Zechun Liu, Yuandong Tian, Harshit Khaitan, Zhangyang Wang, Steven Li |
| 2025 | ICLR | ParamΔ for Direct Mixing: Post-Train Large Language Model At Zero Cost. | Sheng Cao, Mingrui Wu, Karthik Prasad, Yuandong Tian, Zechun Liu |
| 2025 | ICLR | SpinQuant: LLM Quantization with Learned Rotations. | Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort |
| 2025 | ICML | PARQ: Piecewise-Affine Regularized Quantization. | Lisa Jin, Jianhao Ma, Zechun Liu, Andrey Gromov, Aaron Defazio, Lin Xiao |
| 2025 | ICML | 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 |
| 2025 | ICML | 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, Jrgen Schmidhuber |
| 2024 | ACL | 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 |
| 2024 | ACL | 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 |
| 2024 | EMNLP | 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 |
| 2024 | EMNLP | 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 |
| 2024 | EMNLP | RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization. | Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng |
| 2024 | ICASSP | 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 |
| 2024 | ICML | 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 |
| 2023 | ACL | Binary and Ternary Natural Language Generation. | Zechun Liu, Barlas Oguz, Aasish Pappu, Yangyang Shi, Raghuraman Krishnamoorthi |
| 2023 | EMNLP | LLM-FP4: 4-Bit Floating-Point Quantized Transformers. | Shih-Yang Liu, Zechun Liu, Xijie Huang, Pingcheng Dong, Kwang-Ting Cheng |
| 2023 | ICML | Oscillation-free Quantization for Low-bit Vision Transformers. | Shih-Yang Liu, Zechun Liu, Kwang-Ting Cheng |
| 2022 | AAAI | Stereo Neural Vernier Caliper. | Shichao Li, Zechun Liu, Zhiqiang Shen, Kwang-Ting Cheng |
| 2022 | AAAI | Un-mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning. | Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell, Eric Poe Xing |
| 2022 | CVPR | Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. | Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing |
| 2022 | CVPR | Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation. | Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric P. Xing, Zhiqiang Shen |
| 2022 | ECCV | Data-Free Neural Architecture Search via Recursive Label Calibration. | Zechun Liu, Zhiqiang Shen, Yun Long, Eric P. Xing, Kwang-Ting Cheng, Chas Leichner |
| 2022 | ECCV | Sliced Recursive Transformer. | Zhiqiang Shen, Zechun Liu, Eric P. Xing |
| 2022 | ICML | 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 |
| 2021 | AAAI | Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning. | Zhiqiang Shen, Zechun Liu, Jie Qin, Marios Savvides, Kwang-Ting Cheng |
| 2021 | CVPR | "BNN - BN = ?": Training Binary Neural Networks Without Batch Normalization. | Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang |
| 2021 | CVPR | 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 |
| 2021 | ICLR | Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study. | Zhiqiang Shen, Zechun Liu, Dejia Xu, Zitian Chen, Kwang-Ting Cheng, Marios Savvides |
| 2021 | ICML | How Do Adam and Training Strategies Help BNNs Optimization. | Zechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng |
| 2021 | WACV | Conditional Link Prediction of Category-Implicit Keypoint Detection. | Ellen Yi-Ge, Rui Fan, Zechun Liu, Zhiqiang Shen |
| 2020 | CVPR | Binarizing MobileNet via Evolution-Based Searching. | Hai Phan, Zechun Liu, Dang Huynh, Marios Savvides, Kwang-Ting Cheng, Zhiqiang Shen |
| 2020 | ECCV | Single Path One-Shot Neural Architecture Search with Uniform Sampling. | Zichao Guo, Xiangyu Zhang, Haoyuan Mu, Wen Heng, Zechun Liu, Yichen Wei, Jian Sun |
| 2020 | ECCV | ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functions. | Zechun Liu, Zhiqiang Shen, Marios Savvides, Kwang-Ting Cheng |
| 2020 | ECCV | Weight-Dependent Gates for Differentiable Neural Network Pruning. | Yun Li, Weiqun Wu, Zechun Liu, Chi Zhang, Xiangyu Zhang, Haotian Yao, Baoqun Yin |
| 2020 | ICASSP | Attentive Cutmix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification. | Devesh Walawalkar, Zhiqiang Shen, Zechun Liu, Marios Savvides |
| 2019 | ICCV | MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning. | Zechun Liu, Haoyuan Mu, Xiangyu Zhang, Zichao Guo, Xin Yang, Kwang-Ting Cheng, Jian Sun |
| 2018 | ECCV | 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 |