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ORCIDXingchao Liu
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2020 – today
- 2024
[c19]Chengyue Gong, Xiaocong Du, Bhargav Bhushanam, Lemeng Wu, Xingchao Liu, Dhruv Choudhary, Arun Kejariwal, Qiang Liu:
Layer Compression of Deep Networks with Straight Flows. AAAI 2024: 12181-12189- [c18]Xingchao Liu, Xiwen Zhang, Jianzhu Ma, Jian Peng, Qiang Liu:
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation. ICLR 2024 - [c17]Shujian Zhang, Lemeng Wu, Chengyue Gong, Xingchao Liu:
LanguageFlow: Advancing Diffusion Language Generation with Probabilistic Flows. NAACL-HLT 2024: 3893-3905 - [i21]Xixi Hu, Bo Liu, Xingchao Liu, Qiang Liu:
AdaFlow: Imitation Learning with Variance-Adaptive Flow-Based Policies. CoRR abs/2402.04292 (2024) - [i20]Shujian Zhang, Lemeng Wu, Chengyue Gong, Xingchao Liu:
Language Rectified Flow: Advancing Diffusion Language Generation with Probabilistic Flows. CoRR abs/2403.16995 (2024) - [i19]Hanshu Yan, Xingchao Liu, Jiachun Pan, Jun Hao Liew, Qiang Liu, Jiashi Feng:
PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator. CoRR abs/2405.07510 (2024) - [i18]Zhimin Li, Jianwei Zhang, Qin Lin, Jiangfeng Xiong, Yanxin Long, Xinchi Deng, Yingfang Zhang, Xingchao Liu, Minbin Huang, Zedong Xiao, Dayou Chen, Jiajun He, Jiahao Li, Wenyue Li, Chen Zhang, Rongwei Quan, Jianxiang Lu, Jiabin Huang, Xiaoyan Yuan, Xiaoxiao Zheng, Yixuan Li, Jihong Zhang, Chao Zhang, Meng Chen, Jie Liu, Zheng Fang, Weiyan Wang, Jinbao Xue, Yangyu Tao, Jianchen Zhu, Kai Liu, Sihuan Lin, Yifu Sun, Yun Li, Dongdong Wang, Mingtao Chen, Zhichao Hu, Xiao Xiao, Yan Chen, Yuhong Liu, Wei Liu, Di Wang, Yong Yang, Jie Jiang, Qinglin Lu:
Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding. CoRR abs/2405.08748 (2024) - [i17]Ling Yang, Zixiang Zhang, Zhilong Zhang, Xingchao Liu, Minkai Xu, Wentao Zhang, Chenlin Meng, Stefano Ermon, Bin Cui:
Consistency Flow Matching: Defining Straight Flows with Velocity Consistency. CoRR abs/2407.02398 (2024) - [i16]Yuanzhi Zhu, Xingchao Liu, Qiang Liu:
SlimFlow: Training Smaller One-Step Diffusion Models with Rectified Flow. CoRR abs/2407.12718 (2024) - 2023
- [c16]Lemeng Wu, Dilin Wang, Chengyue Gong, Xingchao Liu, Yunyang Xiong, Rakesh Ranjan, Raghuraman Krishnamoorthi, Vikas Chandra, Qiang Liu:
Fast Point Cloud Generation with Straight Flows. CVPR 2023: 9445-9454 - [c15]Xingchao Liu, Lemeng Wu, Shujian Zhang, Chengyue Gong, Wei Ping, Qiang Liu:
FlowGrad: Controlling the Output of Generative ODEs with Gradients. CVPR 2023: 24335-24344 - [c14]Xingchao Liu, Chengyue Gong, Qiang Liu:
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow. ICLR 2023 - [c13]Xingchao Liu, Lemeng Wu, Mao Ye, Qiang Liu:
Learning Diffusion Bridges on Constrained Domains. ICLR 2023 - [c12]Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Grathwohl, Dale Schuurmans, Hanjun Dai:
DISCS: A Benchmark for Discrete Sampling. NeurIPS 2023 - [i15]Shujian Zhang, Chengyue Gong, Lemeng Wu, Xingchao Liu, Mingyuan Zhou:
AutoML-GPT: Automatic Machine Learning with GPT. CoRR abs/2305.02499 (2023) - [i14]Xingchao Liu, Xiwen Zhang, Jianzhu Ma, Jian Peng, Qiang Liu:
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation. CoRR abs/2309.06380 (2023) - 2022
- [c11]Shujian Zhang, Chengyue Gong, Xingchao Liu:
Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models. EMNLP 2022: 3931-3943 - [c10]Ruqi Zhang, Xingchao Liu, Qiang Liu:
A Langevin-like Sampler for Discrete Distributions. ICML 2022: 26375-26396 - [c9]Shujian Zhang, Chengyue Gong, Xingchao Liu, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
ALLSH: Active Learning Guided by Local Sensitivity and Hardness. NAACL-HLT (Findings) 2022: 1328-1342 - [c8]Lemeng Wu, Chengyue Gong, Xingchao Liu, Mao Ye, Qiang Liu:
Diffusion-based Molecule Generation with Informative Prior Bridges. NeurIPS 2022 - [i13]Shujian Zhang, Chengyue Gong, Xingchao Liu, Pengcheng He, Weizhu Chen, Mingyuan Zhou:
ALLSH: Active Learning Guided by Local Sensitivity and Hardness. CoRR abs/2205.04980 (2022) - [i12]Ruqi Zhang, Xingchao Liu, Qiang Liu:
A Langevin-like Sampler for Discrete Distributions. CoRR abs/2206.09914 (2022) - [i11]Xingchao Liu, Lemeng Wu, Mao Ye, Qiang Liu:
Let us Build Bridges: Understanding and Extending Diffusion Generative Models. CoRR abs/2208.14699 (2022) - [i10]Lemeng Wu, Chengyue Gong, Xingchao Liu, Mao Ye, Qiang Liu:
Diffusion-based Molecule Generation with Informative Prior Bridges. CoRR abs/2209.00865 (2022) - [i9]Xingchao Liu, Chengyue Gong, Qiang Liu:
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow. CoRR abs/2209.03003 (2022) - [i8]Yan Zheng, Lemeng Wu, Xingchao Liu, Zhen Chen, Qiang Liu, Qixing Huang:
Neural Volumetric Mesh Generator. CoRR abs/2210.03158 (2022) - [i7]Shujian Zhang, Chengyue Gong, Xingchao Liu:
Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models. CoRR abs/2211.00915 (2022) - [i6]Lemeng Wu, Dilin Wang, Chengyue Gong, Xingchao Liu, Yunyang Xiong, Rakesh Ranjan, Raghuraman Krishnamoorthi, Vikas Chandra, Qiang Liu:
Fast Point Cloud Generation with Straight Flows. CoRR abs/2212.01747 (2022) - 2021
- [c7]Xingchao Liu, Mao Ye, Dengyong Zhou, Qiang Liu:
Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision. AAAI 2021: 8697-8705 - [c6]Xingchao Liu, Xin Tong, Qiang Liu:
Profiling Pareto Front With Multi-Objective Stein Variational Gradient Descent. NeurIPS 2021: 14721-14733 - [c5]Bo Liu, Xingchao Liu, Xiaojie Jin, Peter Stone, Qiang Liu:
Conflict-Averse Gradient Descent for Multi-task learning. NeurIPS 2021: 18878-18890 - [c4]Xingchao Liu, Xin Tong, Qiang Liu:
Sampling with Trusthworthy Constraints: A Variational Gradient Framework. NeurIPS 2021: 23557-23568 - [c3]Chengyue Gong, Xingchao Liu, Qiang Liu:
Automatic and Harmless Regularization with Constrained and Lexicographic Optimization: A Dynamic Barrier Approach. NeurIPS 2021: 29630-29642 - [i5]Lemeng Wu, Xingchao Liu, Qiang Liu:
Centroid Transformers: Learning to Abstract with Attention. CoRR abs/2102.08606 (2021) - [i4]Bo Liu, Xingchao Liu, Xiaojie Jin, Peter Stone, Qiang Liu:
Conflict-Averse Gradient Descent for Multi-task Learning. CoRR abs/2110.14048 (2021) - [i3]Xingchao Liu, Chengyue Gong, Lemeng Wu, Shujian Zhang, Hao Su, Qiang Liu:
FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimization. CoRR abs/2112.01573 (2021) - 2020
- [c2]Xingchao Liu, Xing Han, Na Zhang, Qiang Liu:
Certified Monotonic Neural Networks. NeurIPS 2020 - [i2]Xingchao Liu, Mao Ye, Dengyong Zhou, Qiang Liu:
Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision. CoRR abs/2002.09049 (2020) - [i1]Xingchao Liu, Xing Han, Na Zhang, Qiang Liu:
Certified Monotonic Neural Networks. CoRR abs/2011.10219 (2020)
2010 – 2019
- 2019
- [c1]Xingchao Liu, Ce Li, Hongren Wang, Xiantong Zhen, Baochang Zhang, Qixiang Ye:
Starts Better and Ends Better: A Target Adaptive Image Signature Tracker. WACV 2019: 171-178 - 2018
- [j1]Ce Li
, Xingchao Liu, Xiangbo Su, Baochang Zhang:
Robust kernelized correlation filter with scale adaption for real-time single object tracking. J. Real Time Image Process. 15(3): 583-596 (2018)
Coauthor Index
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last updated on 2024-08-30 20:42 CEST by the dblp team
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