Topic medical concept embedding: Multi-sense representation learning for medical concept. - Feng Qian; ChengYue Gong; Luchen Liu; Lei Sha; Ming Zhang 004 (BIBM, 2017)

Deep Dynamic Poisson Factorization Model. - ChengYue Gong; Win-Bin Huang (NIPS, 2017)

Neural User Response Generator: Fake News Detection with Collective User Intelligence. - Feng Qian; ChengYue Gong; Karishma Sharma; Yan Liu 002 (IJCAI, 2018)

FRAGE: Frequency-Agnostic Word Representation. - ChengYue Gong; Di He 001; Xu Tan 003; Tao Qin 001; Liwei Wang 001; Tie-Yan Liu (NeurIPS, 2018)

Sentence-Wise Smooth Regularization for Sequence to Sequence Learning. - ChengYue Gong; Xu Tan 003; Di He 001; Tao Qin 001 (AAAI, 2019)

Mixed Precision Neural Architecture Search for Energy Efficient Deep Learning. - ChengYue Gong; Zixuan Jiang; Dilin Wang; Yibo Lin; Qiang Liu 001; David Z. Pan (ICCAD, 2019)

Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization. - ChengYue Gong; Jian Peng 001; Qiang Liu 001 (ICML, 2019)

Improving Neural Language Modeling via Adversarial Training. - Dilin Wang; ChengYue Gong; Qiang Liu 001 (ICML, 2019)

SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions. - Mao Ye 006; Chengyue Gong; Qiang Liu 001 (ACL, 2020)

Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection. - Mao Ye 006; Chengyue Gong; Lizhen Nie; Denny Zhou; Adam R. Klivans; Qiang Liu 001 (ICML, 2020)

Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework. - Dinghuai Zhang; Mao Ye 006; Chengyue Gong; Zhanxing Zhu; Qiang Liu 001 (NeurIPS, 2020)

MaxUp: A Simple Way to Improve Generalization of Neural Network Training. - ChengYue Gong; Tongzheng Ren; Mao Ye 006; Qiang Liu 001 (CoRR, 2020)

Knowing More About Questions Can Help: Improving Calibration in Question Answering. - Shujian Zhang; Chengyue Gong; Eunsol Choi (ACL/IJCNLP (Findings), 2021)

MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training. - Chengyue Gong; Tongzheng Ren; Mao Ye 006; Qiang Liu 001 (CVPR, 2021)

AlphaMatch: Improving Consistency for Semi-Supervised Learning With Alpha-Divergence. - Chengyue Gong; Dilin Wang; Qiang Liu 001 (CVPR, 2021)

KeepAugment: A Simple Information-Preserving Data Augmentation Approach. - Chengyue Gong; Dilin Wang; Meng Li 004; Vikas Chandra; Qiang Liu 001 (CVPR, 2021)

AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling. - Dilin Wang; Meng Li 004; Chengyue Gong; Vikas Chandra (CVPR, 2021)

Learning with Different Amounts of Annotation: From Zero to Many Labels. - Shujian Zhang; Chengyue Gong; Eunsol Choi (EMNLP (1), 2021)

AlphaNet: Improved Training of Supernets with Alpha-Divergence. - Dilin Wang; Chengyue Gong; Meng Li 004; Qiang Liu 001; Vikas Chandra (ICML, 2021)

Automatic and Harmless Regularization with Constrained and Lexicographic Optimization: A Dynamic Barrier Approach. - Chengyue Gong; Xingchao Liu; Qiang Liu 001 (NeurIPS, 2021)

argmax centroid. - Chengyue Gong; Mao Ye 006; Qiang Liu 001 (NeurIPS, 2021)

Capturing Label Distribution: A Case Study in NLI. - Shujian Zhang; Chengyue Gong; Eunsol Choi (CoRR, 2021)

AlphaNet: Improved Training of Supernet with Alpha-Divergence. - Dilin Wang; Chengyue Gong; Meng Li 004; Qiang Liu 001; Vikas Chandra (CoRR, 2021)

Improve Vision Transformers Training by Suppressing Over-smoothing. - Chengyue Gong; Dilin Wang; Meng Li 004; Vikas Chandra; Qiang Liu 001 (CoRR, 2021)

FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimization. - Xingchao Liu; Chengyue Gong; Lemeng Wu; Shujian Zhang; Hao Su; Qiang Liu 001 (CoRR, 2021)

Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models. - Shujian Zhang; Chengyue Gong; Xingchao Liu (EMNLP, 2022)

NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training. - Chengyue Gong; Dilin Wang; Meng Li 004; Xinlei Chen; Zhicheng Yan 001; Yuandong Tian; Qiang Liu 001; Vikas Chandra (ICLR, 2022)

How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity. - Chengyue Gong; Lemeng Wu; Qiang Liu 001 (ICML, 2022)

Harmless Transfer Learning for Item Embeddings. - Chengyue Gong; Xiaocong Du; Dhruv Choudhary; Bhargav Bhushanam; Qiang Liu 001; Arun Kejariwal (NAACL-HLT (Findings), 2022)

ALLSH: Active Learning Guided by Local Sensitivity and Hardness. - Shujian Zhang; Chengyue Gong; Xingchao Liu; Pengcheng He; Weizhu Chen; Mingyuan Zhou (NAACL-HLT (Findings), 2022)

Diffusion-based Molecule Generation with Informative Prior Bridges. - Lemeng Wu; Chengyue Gong; Xingchao Liu; Mao Ye 006; Qiang Liu 001 (NeurIPS, 2022)

FlowGrad: Controlling the Output of Generative ODEs with Gradients. - Xingchao Liu; Lemeng Wu; Shujian Zhang; Chengyue Gong; Wei Ping; Qiang Liu 001 (CVPR, 2023)

Fast Point Cloud Generation with Straight Flows. - Lemeng Wu; Dilin Wang; Chengyue Gong; Xingchao Liu; Yunyang Xiong; Rakesh Ranjan; Raghuraman Krishnamoorthi; Vikas Chandra; Qiang Liu 001 (CVPR, 2023)

HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing. - Tianlong Chen 001; Chengyue Gong; Daniel Jesus Diaz; Xuxi Chen; Jordan Tyler Wells; Qiang Liu 001; Zhangyang Wang; Andrew D. Ellington; Alex Dimakis; Adam R. Klivans (ICLR, 2023)

Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow. - Xingchao Liu; Chengyue Gong; Qiang Liu 001 (ICLR, 2023)

AutoML-GPT: Automatic Machine Learning with GPT. - Shujian Zhang; Chengyue Gong; Lemeng Wu; Xingchao Liu; Mingyuan Zhou (CoRR, 2023)

Layer Compression of Deep Networks with Straight Flows. - Chengyue Gong; Xiaocong Du; Bhargav Bhushanam; Lemeng Wu; Xingchao Liu; Dhruv Choudhary; Arun Kejariwal; Qiang Liu 001 (AAAI, 2024)

Evolution-Inspired Loss Functions for Protein Representation Learning. - Chengyue Gong; Adam R. Klivans; James Loy; Tianlong Chen 001; Qiang Liu 001; Daniel Jesus Diaz (ICML, 2024)

Switchable Decision: Dynamic Neural Generation Networks. - Shujian Zhang; Korawat Tanwisuth; Chengyue Gong; Pengcheng He; Mingyuan Zhou (ICML, 2024)

LanguageFlow: Advancing Diffusion Language Generation with Probabilistic Flows. - Shujian Zhang; Lemeng Wu; Chengyue Gong; Xingchao Liu (NAACL-HLT, 2024)

Language Rectified Flow: Advancing Diffusion Language Generation with Probabilistic Flows. - Shujian Zhang; Lemeng Wu; Chengyue Gong; Xingchao Liu (CoRR, 2024)

Rectified Flow For Structure Based Drug Design. - Daiheng Zhang; Chengyue Gong; Qiang Liu 001 (CoRR, 2024)

Distilling Structural Representations into Protein Sequence Models. - Jeffrey Ouyang-Zhang; Chengyue Gong; Yue Zhao 006; Philipp Krähenbühl; Adam R. Klivans; Daniel Jesus Diaz (ICLR, 2025)

NRFlow: Towards Noise-Robust Generative Modeling via High-Order Mechanism. - Bo Chen 029; Chengyue Gong; Xiaoyu Li 001; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002; Mingda Wan; Xugang Ye (UAI, 2025)

RichSpace: Enriching Text-to-Video Prompt Space via Text Embedding Interpolation. - Yuefan Cao; Chengyue Gong; Xiaoyu Li 001; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002 (CoRR, 2025)

High-Order Matching for One-Step Shortcut Diffusion Models. - Bo Chen 029; Chengyue Gong; Xiaoyu Li 001; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002; Mingda Wan (CoRR, 2025)

On Computational Limits of FlowAR Models: Expressivity and Efficiency. - Chengyue Gong; Yekun Ke; Xiaoyu Li 001; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002 (CoRR, 2025)

Theoretical Guarantees for High Order Trajectory Refinement in Generative Flows. - Chengyue Gong; Xiaoyu Li 001; Yingyu Liang; Jiangxuan Long 001; Zhenmei Shi; Zhao Song 002; Yu Tian (CoRR, 2025)

Protenix-Mini: Efficient Structure Predictor via Compact Architecture, Few-Step Diffusion and Switchable pLM. - Chengyue Gong; Xinshi Chen; Yuxuan Zhang; Yuxuan Song; Hao Zhou; Wenzhi Xiao (CoRR, 2025)