MatryoshkaKV: Adaptive KV Compression via Trainable Orthogonal Projection
Bokai Lin, Zihao Zeng, Zipeng Xiao, Siqi Kou, TianQi Hou, Xiaofeng Gao, Hao Zhang, Zhijie Deng†
ICLR 2025

3D-Properties: Identifying Challenges in DPO and Charting a Path Forward
Yuzi Yan, Yibo Miao, Jialian Li, Yipin Zhang, Jian Xie, Zhijie Deng†, Dong Yan†
ICLR 2025

SCott: Accelerating Diffusion Models with Stochastic Consistency Distillation
Hongjian Liu, Qingsong Xie†, Zhijie Deng†, Chen Chen, Shixiang Tang, Fueyang Fu, Zheng-jun Zha, Haonan Lu
AAAI 2025

Unveiling Uncertainty: A Deep Dive into Calibration and Performance of Multimodal Large Language Models
Zijun Chen, Wenbo Hu, Guande He, Zhijie Deng, Zheng Zhang, Richang Hong
Coling 2025

Amortized Fourier Neural Operators
Zipeng Xiao, Siqi Kou, Zhongkai Hao, Bokai Lin, Zhijie Deng†
NeurIPS 2024

AdaMOE: Token-Adaptive Routing with Null Experts for Mixture-of-Experts Language Models
Zihao Zeng, Yibo Miao, Hongcheng Gao, Hao Zhang, Zhijie Deng†
Findings of EMNLP 2024

Calibrating Deep Ensemble through Functional Variational Inference
Zhijie Deng, Feng Zhou, Jianfei Chen, Guoqiang Wu, Jun Zhu
TMLR 2024

Accurate and Reliable Forecasting using Stochastic Differential Equations
Peng Cui, Zhijie Deng, Wenbo Hu, Jun Zhu
TKDD 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†
ECCV 2024

Efficient Detection of LLM-generated Texts with a Bayesian Surrogate Model
Yibo Miao, Hongcheng Gao, Hao Zhang, Zhijie Deng†
Findings of ACL 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
ICML 2024

CLLMs: Consistency Large Language Models
Siqi Kou, Lanxiang Hu, Zhezhi He, Zhijie Deng†, Hao Zhang
ICML 2024
[code]

Improved Operator Learning by Orthogonal Attention
Zipeng Xiao, Zhongkai Hao, Bokai Lin, Zhijie Deng†, Hang Su†
ICML 2024 (Spotlight)

Online Speculative Decoding
Xiaoxuan Liu, Lanxiang Hu, Peter Bailis, Ion Stoica, Zhijie Deng†, Alvin Cheung, Hao Zhang†
ICML 2024

LOVECon: Text-driven Training-Free Long Video Editing with ControlNet
Zhenyi Liao, Zhijie Deng†
AI for Content Creation Workshop @ CVPR 2024

Bayesian Exploration of Pre-trained Models for Low-shot Image Classification
Yibo Miao, Yu Lei, Feng Zhou†, Zhijie Deng†
CVPR 2024

BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference
Siqi Kou, Lei Gan, Dequan Wang, Chongxuan Li†, Zhijie Deng†
ICLR 2024

Towards Accelerated Model Training via Bayesian Data Selection
Zhijie Deng*, Peng Cui*, Jun Zhu
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

Heterogeneous Multi-Task Gaussian Cox Processes
Feng Zhou, Quyu Kong, Zhijie Deng, Fengxiang He, Peng Cui, Jun Zhu
Machine Learning 2023

Learning Neural Eigenfunctions for Unsupervised Semantic Segmentation
Zhijie Deng, Yucen Luo
ICCV 2023
[code]

Batch Virtual Adversarial Training for Graph Convolutional Networks
Zhijie Deng, Yinpeng Dong, Jun Zhu
AI Open 2023
[code]

BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-tuning
Zhijie Deng, Jun Zhu
ACML 2022
[code]

Accelerated Linearized Laplace Approximation for Bayesian Deep Learning
Zhijie Deng, Feng Zhou, Jun Zhu
NeurIPS 2022 (Spotlight)
[code]

Confidence-based Reliable Learning under Dual Noises
Peng Cui, Yang Yue, Zhijie Deng†, Jun Zhu†
NeurIPS 2022

Efficient Inference for Dynamic Flexible Interactions of Neural Populations
Feng Zhou, Quyu Kong, Zhijie Deng, Jichao Kan, Yixuan Zhang, Cheng Feng, Jun Zhu
JMLR 2022

NeuralEF: Deconstructing Kernels by Deep Neural Networks
Zhijie Deng, Jiaxin Shi, Jun Zhu
ICML 2022

Exploring Memorization in Adversarial Training
Yinpeng Dong, Ke Xu, Xiao Yang, Tianyu Pang, Zhijie Deng, Hang Su, Jun Zhu
ICLR 2022

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
ICCV 2021

LiBRe: A Practical Bayesian Approach to Adversarial Detection
Zhijie Deng, Xiao Yang, Shizhen Xu, Hang Su, Jun Zhu
CVPR 2021 (Valse 2021 Spotlight, 2021.10)
[code]

Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structure
Zhijie Deng, Yucen Luo, Jun Zhu
2nd Workshop on Neural Architecture Search at ICLR 2021

Adversarial Distributional Training for Robust Deep Learning
Yinpeng Dong*, Zhijie Deng*, Tianyu Pang, Hang Su, Jun Zhu
NeurIPS 2020
[code]

Understanding and Exploring the Network with Stochastic Architectures
Zhijie Deng, Yinpeng Dong, Shifeng Zhang, Jun Zhu
NeurIPS 2020
[code]

Autosync: Learning to Synchronize for Data-parallel Distributed Deep Learning
Hao Zhang*, Yuan Li*, Zhijie Deng, Xiaodan Liang, Lawrence Carin, Eric Xing
NeurIPS 2020
[code]

Cluster Alignment with a Teacher for Unsupervised Domain Adaptation
Zhijie Deng, Yucen Luo, Jun Zhu
ICCV 2019
[code]

Cavs: An Efficient Runtime System for Dynamic Neural Networks
Shizhen Xu*, Hao Zhang*, Graham Neubig, Wei Dai, Jin Kyu Kim, Zhijie Deng, Qirong Ho, Guangwen Yang, Eric P Xing
ATC 2018
[code]

Structured Generative Adversarial Networks
Zhijie Deng*, Hao Zhang*, Xiaodan Liang, Luona Yang, Shizhen Xu, Jun Zhu, Eric P Xing
NeurIPS 2017 (Nvidia Pioneer Research Award)
[code]