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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