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ORCIDChengyue Gong
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2020 – today
- 2024
[c34]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- [c33]Chengyue Gong, Adam R. Klivans, James Loy, Tianlong Chen, Qiang Liu, Daniel Jesus Diaz:
Evolution-Inspired Loss Functions for Protein Representation Learning. ICML 2024 - [c32]Shujian Zhang, Korawat Tanwisuth, Chengyue Gong, Pengcheng He, Mingyuan Zhou:
Switchable Decision: Dynamic Neural Generation Networks. ICML 2024 - [c31]Shujian Zhang, Lemeng Wu, Chengyue Gong, Xingchao Liu:
LanguageFlow: Advancing Diffusion Language Generation with Probabilistic Flows. NAACL-HLT 2024: 3893-3905 - [i25]Shujian Zhang, Lemeng Wu, Chengyue Gong, Xingchao Liu:
Language Rectified Flow: Advancing Diffusion Language Generation with Probabilistic Flows. CoRR abs/2403.16995 (2024) - [i24]Shujian Zhang, Korawat Tanwisuth, Chengyue Gong, Pengcheng He, Mingyuan Zhou:
Switchable Decision: Dynamic Neural Generation Networks. CoRR abs/2405.04513 (2024) - 2023
- [c30]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 - [c29]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 - [c28]Tianlong Chen, Chengyue Gong, Daniel Jesus Diaz, Xuxi Chen, Jordan Tyler Wells, Qiang Liu, Zhangyang Wang, Andrew D. Ellington, Alex Dimakis, Adam R. Klivans:
HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing. ICLR 2023 - [c27]Xingchao Liu, Chengyue Gong, Qiang Liu:
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow. ICLR 2023 - [i23]Shujian Zhang, Chengyue Gong, Lemeng Wu, Xingchao Liu, Mingyuan Zhou:
AutoML-GPT: Automatic Machine Learning with GPT. CoRR abs/2305.02499 (2023) - 2022
- [c26]Shujian Zhang, Chengyue Gong, Xingchao Liu:
Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models. EMNLP 2022: 3931-3943 - [c25]Chengyue Gong, Dilin Wang, Meng Li, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra:
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training. ICLR 2022 - [c24]Chengyue Gong, Lemeng Wu, Qiang Liu:
How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity. ICML 2022: 7650-7664 - [c23]Chengyue Gong, Xiaocong Du, Dhruv Choudhary, Bhargav Bhushanam, Qiang Liu, Arun Kejariwal:
Harmless Transfer Learning for Item Embeddings. NAACL-HLT (Findings) 2022: 504-516 - [c22]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 - [c21]Lemeng Wu, Chengyue Gong, Xingchao Liu, Mao Ye, Qiang Liu:
Diffusion-based Molecule Generation with Informative Prior Bridges. NeurIPS 2022 - [i22]Chengyue Gong, Lemeng Wu, Qiang Liu:
How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity. CoRR abs/2202.08376 (2022) - [i21]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) - [i20]Lemeng Wu, Chengyue Gong, Xingchao Liu, Mao Ye, Qiang Liu:
Diffusion-based Molecule Generation with Informative Prior Bridges. CoRR abs/2209.00865 (2022) - [i19]Xingchao Liu, Chengyue Gong, Qiang Liu:
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow. CoRR abs/2209.03003 (2022) - [i18]Shujian Zhang, Chengyue Gong, Xingchao Liu:
Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models. CoRR abs/2211.00915 (2022) - [i17]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
- [c20]Shujian Zhang, Chengyue Gong, Eunsol Choi:
Knowing More About Questions Can Help: Improving Calibration in Question Answering. ACL/IJCNLP (Findings) 2021: 1958-1970 - [c19]Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu:
KeepAugment: A Simple Information-Preserving Data Augmentation Approach. CVPR 2021: 1055-1064 - [c18]Chengyue Gong, Tongzheng Ren, Mao Ye, Qiang Liu:
MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training. CVPR 2021: 2474-2483 - [c17]Dilin Wang, Meng Li, Chengyue Gong, Vikas Chandra:
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling. CVPR 2021: 6418-6427 - [c16]Chengyue Gong, Dilin Wang, Qiang Liu:
AlphaMatch: Improving Consistency for Semi-Supervised Learning With Alpha-Divergence. CVPR 2021: 13683-13692 - [c15]Shujian Zhang, Chengyue Gong, Eunsol Choi:
Learning with Different Amounts of Annotation: From Zero to Many Labels. EMNLP (1) 2021: 7620-7632 - [c14]Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra:
AlphaNet: Improved Training of Supernets with Alpha-Divergence. ICML 2021: 10760-10771 - [c13]Chengyue Gong, Mao Ye, Qiang Liu:
argmax centroid. NeurIPS 2021: 7012-7024 - [c12]Chengyue Gong, Xingchao Liu, Qiang Liu:
Automatic and Harmless Regularization with Constrained and Lexicographic Optimization: A Dynamic Barrier Approach. NeurIPS 2021: 29630-29642 - [i16]Shujian Zhang, Chengyue Gong, Eunsol Choi:
Capturing Label Distribution: A Case Study in NLI. CoRR abs/2102.06859 (2021) - [i15]Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra:
AlphaNet: Improved Training of Supernet with Alpha-Divergence. CoRR abs/2102.07954 (2021) - [i14]Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu:
Improve Vision Transformers Training by Suppressing Over-smoothing. CoRR abs/2104.12753 (2021) - [i13]Shujian Zhang, Chengyue Gong, Eunsol Choi:
Knowing More About Questions Can Help: Improving Calibration in Question Answering. CoRR abs/2106.01494 (2021) - [i12]Shujian Zhang, Chengyue Gong, Eunsol Choi:
Learning with Different Amounts of Annotation: From Zero to Many Labels. CoRR abs/2109.04408 (2021) - [i11]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
- [c11]Mao Ye, Chengyue Gong, Qiang Liu:
SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions. ACL 2020: 3465-3475 - [c10]Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou, Adam R. Klivans, Qiang Liu:
Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection. ICML 2020: 10820-10830 - [c9]Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu:
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework. NeurIPS 2020 - [i10]ChengYue Gong, Tongzheng Ren, Mao Ye, Qiang Liu:
MaxUp: A Simple Way to Improve Generalization of Neural Network Training. CoRR abs/2002.09024 (2020) - [i9]Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu:
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework. CoRR abs/2002.09169 (2020) - [i8]Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou, Adam R. Klivans, Qiang Liu:
Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection. CoRR abs/2003.01794 (2020) - [i7]Mao Ye, Chengyue Gong, Qiang Liu:
SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions. CoRR abs/2005.14424 (2020) - [i6]Dilin Wang, Meng Li, Chengyue Gong, Vikas Chandra:
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling. CoRR abs/2011.09011 (2020) - [i5]Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu:
KeepAugment: A Simple Information-Preserving Data Augmentation Approach. CoRR abs/2011.11778 (2020) - [i4]Chengyue Gong, Dilin Wang, Qiang Liu:
AlphaMatch: Improving Consistency for Semi-supervised Learning with Alpha-divergence. CoRR abs/2011.11779 (2020)
2010 – 2019
- 2019
- [c8]ChengYue Gong, Xu Tan, Di He, Tao Qin:
Sentence-Wise Smooth Regularization for Sequence to Sequence Learning. AAAI 2019: 6449-6456 - [c7]ChengYue Gong, Zixuan Jiang
, Dilin Wang, Yibo Lin, Qiang Liu, David Z. Pan:
Mixed Precision Neural Architecture Search for Energy Efficient Deep Learning. ICCAD 2019: 1-7 - [c6]ChengYue Gong, Jian Peng, Qiang Liu:
Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization. ICML 2019: 2347-2356 - [c5]Dilin Wang, ChengYue Gong, Qiang Liu:
Improving Neural Language Modeling via Adversarial Training. ICML 2019: 6555-6565 - [i3]Dilin Wang, ChengYue Gong, Qiang Liu:
Improving Neural Language Modeling via Adversarial Training. CoRR abs/1906.03805 (2019) - 2018
- [c4]Feng Qian, ChengYue Gong, Karishma Sharma, Yan Liu:
Neural User Response Generator: Fake News Detection with Collective User Intelligence. IJCAI 2018: 3834-3840 - [c3]ChengYue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu:
FRAGE: Frequency-Agnostic Word Representation. NeurIPS 2018: 1341-1352 - [i2]ChengYue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu:
FRAGE: Frequency-Agnostic Word Representation. CoRR abs/1809.06858 (2018) - [i1]ChengYue Gong, Xu Tan, Di He, Tao Qin:
Sentence-wise Smooth Regularization for Sequence to Sequence Learning. CoRR abs/1812.04784 (2018) - 2017
- [c2]Feng Qian, ChengYue Gong, Luchen Liu, Lei Sha, Ming Zhang:
Topic medical concept embedding: Multi-sense representation learning for medical concept. BIBM 2017: 404-409 - [c1]ChengYue Gong, Win-Bin Huang:
Deep Dynamic Poisson Factorization Model. NIPS 2017: 1666-1674
Coauthor Index
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last updated on 2024-10-07 21:19 CEST by the dblp team
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