Deng, Zhijie

35 publications

ICLR 2025 3D-Properties: Identifying Challenges in DPO and Charting a Path Forward Yuzi Yan, Yibo Miao, Jialian Li, YipinZhang, Jian Xie, Zhijie Deng, Dong Yan
NeurIPS 2025 Adaptive Discretization for Consistency Models Jiayu Bai, Zhanbo Feng, Zhijie Deng, TianQi Hou, Robert C Qiu, Zenan Ling
ICCV 2025 Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation Yu Lei, Bingde Liu, Qingsong Xie, Haonan Lu, Zhijie Deng
ICLR 2025 MatryoshkaKV: Adaptive KV Compression via Trainable Orthogonal Projection Bokai Lin, Zihao Zeng, Zipeng Xiao, Siqi Kou, TianQi Hou, Xiaofeng Gao, Hao Zhang, Zhijie Deng
ICCV 2025 Meta-Unlearning on Diffusion Models: Preventing Relearning Unlearned Concepts Hongcheng Gao, Tianyu Pang, Chao Du, Taihang Hu, Zhijie Deng, Min Lin
ICML 2025 Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads Siqi Kou, Jiachun Jin, Zhihong Liu, Chang Liu, Ye Ma, Jian Jia, Quan Chen, Peng Jiang, Zhijie Deng
AAAI 2025 SCott: Accelerating Diffusion Models with Stochastic Consistency Distillation Hongjian Liu, Qingsong Xie, Tianxiang Ye, Zhijie Deng, Chen Chen, Shixiang Tang, Xueyang Fu, Haonan Lu, Zheng-Jun Zha
NeurIPS 2025 Scaling Speculative Decoding with Lookahead Reasoning Yichao Fu, Rui Ge, Zelei Shao, Zhijie Deng, Hao Zhang
NeurIPS 2025 Which Data Attributes Stimulate Math and Code Reasoning? an Investigation via Influence Functions Siqi Kou, Qingyuan Tian, Hanwen Xu, Zihao Zeng, Zhijie Deng
NeurIPS 2024 Amortized Fourier Neural Operators Zipeng Xiao, Siqi Kou, Zhongkai Hao, Bokai Lin, Zhijie Deng
ICLR 2024 BayesDiff: Estimating Pixel-Wise Uncertainty in Diffusion via Bayesian Inference Siqi Kou, Lei Gan, Dequan Wang, Chongxuan Li, Zhijie Deng
CVPR 2024 Bayesian Exploration of Pre-Trained Models for Low-Shot Image Classification Yibo Miao, Yu Lei, Feng Zhou, Zhijie Deng
ICML 2024 CLLMs: Consistency Large Language Models Siqi Kou, Lanxiang Hu, Zhezhi He, Zhijie Deng, Hao Zhang
TMLR 2024 Calibrating Deep Ensemble Through Functional Variational Inference Zhijie Deng, Feng Zhou, Jianfei Chen, Guoqiang Wu, Jun Zhu
ICML 2024 Improved Operator Learning by Orthogonal Attention Zipeng Xiao, Zhongkai Hao, Bokai Lin, Zhijie Deng, Hang Su
ECCV 2024 Lost in Translation: Latent Concept Misalignment in Text-to-Image Diffusion Models Juntu Zhao, Junyu Deng, Yixin Ye, Chongxuan Li, Zhijie Deng, Dequan Wang
ICML 2024 Online Speculative Decoding Xiaoxuan Liu, Lanxiang Hu, Peter Bailis, Alvin Cheung, Zhijie Deng, Ion Stoica, Hao Zhang
ICML 2024 SpikeZIP-TF: Conversion Is All You Need for Transformer-Based SNN Kang You, Zekai Xu, Chen Nie, Zhijie Deng, Qinghai Guo, Xiang Wang, Zhezhi He
MLJ 2023 Heterogeneous Multi-Task Gaussian Cox Processes Feng Zhou, Quyu Kong, Zhijie Deng, Fengxiang He, Peng Cui, Jun Zhu
ICCV 2023 Learning Neural Eigenfunctions for Unsupervised Semantic Segmentation Zhijie Deng, Yucen Luo
NeurIPS 2023 Learning Sample Difficulty from Pre-Trained Models for Reliable Prediction Peng Cui, Dan Zhang, Zhijie Deng, Yinpeng Dong, Jun Zhu
NeurIPS 2023 On Calibrating Diffusion Probabilistic Models Tianyu Pang, Cheng Lu, Chao Du, Min Lin, Shuicheng Yan, Zhijie Deng
NeurIPS 2023 Towards Accelerated Model Training via Bayesian Data Selection Zhijie Deng, Peng Cui, Jun Zhu
NeurIPS 2022 Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng, Feng Zhou, Jun Zhu
ACML 2022 BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-Tuning Zhijie Deng, Jun Zhu
NeurIPS 2022 Confidence-Based Reliable Learning Under Dual Noises Peng Cui, Yang Yue, Zhijie Deng, Jun Zhu
JMLR 2022 Efficient Inference for Dynamic Flexible Interactions of Neural Populations Feng Zhou, Quyu Kong, Zhijie Deng, Jichao Kan, Yixuan Zhang, Cheng Feng, Jun Zhu
ICLR 2022 Exploring Memorization in Adversarial Training Yinpeng Dong, Ke Xu, Xiao Yang, Tianyu Pang, Zhijie Deng, Hang Su, Jun Zhu
ICML 2022 NeuralEF: Deconstructing Kernels by Deep Neural Networks Zhijie Deng, Jiaxin Shi, Jun Zhu
ICCV 2021 Black-Box Detection of Backdoor Attacks with Limited Information and Data Yinpeng Dong, Xiao Yang, Zhijie Deng, Tianyu Pang, Zihao Xiao, Hang Su, Jun Zhu
CVPR 2021 LiBRe: A Practical Bayesian Approach to Adversarial Detection Zhijie Deng, Xiao Yang, Shizhen Xu, Hang Su, Jun Zhu
NeurIPS 2020 Adversarial Distributional Training for Robust Deep Learning Yinpeng Dong, Zhijie Deng, Tianyu Pang, Jun Zhu, Hang Su
NeurIPS 2020 AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep Learning Hao Zhang, Yuan Li, Zhijie Deng, Xiaodan Liang, Lawrence Carin, Eric P. Xing
NeurIPS 2020 Understanding and Exploring the Network with Stochastic Architectures Zhijie Deng, Yinpeng Dong, Shifeng Zhang, Jun Zhu
NeurIPS 2017 Structured Generative Adversarial Networks Zhijie Deng, Hao Zhang, Xiaodan Liang, Luona Yang, Shizhen Xu, Jun Zhu, Eric P Xing