Capturing Conditional Dependence via Auto-regressive Diffusion Models
Fuente:
arXiv
Saved in:
| Main Authors: | Huang, Xunpeng, Han, Yujin, Zou, Difan, Ma, Yian, Zhang, Tong |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Faster Sampling without Isoperimetry via Diffusion-based Monte Carlo
by: Huang, Xunpeng, et al.
Published: (2024)
by: Huang, Xunpeng, et al.
Published: (2024)
On the $ε$-Free Inference Complexity of Absorbing Discrete Diffusion
by: Huang, Xunpeng, et al.
Published: (2025)
by: Huang, Xunpeng, et al.
Published: (2025)
Almost Linear Convergence under Minimal Score Assumptions: Quantized Transition Diffusion
by: Huang, Xunpeng, et al.
Published: (2025)
by: Huang, Xunpeng, et al.
Published: (2025)
An Improved Analysis of Langevin Algorithms with Prior Diffusion for Non-Log-Concave Sampling
by: Huang, Xunpeng, et al.
Published: (2024)
by: Huang, Xunpeng, et al.
Published: (2024)
Faster Sampling via Stochastic Gradient Proximal Sampler
by: Huang, Xunpeng, et al.
Published: (2024)
by: Huang, Xunpeng, et al.
Published: (2024)
Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference
by: Huang, Xunpeng, et al.
Published: (2024)
by: Huang, Xunpeng, et al.
Published: (2024)
Multi-Step Consistency Models: Fast Generation with Theoretical Guarantees
by: Jain, Nishant, et al.
Published: (2025)
by: Jain, Nishant, et al.
Published: (2025)
Improving Group Robustness on Spurious Correlation Requires Preciser Group Inference
by: Han, Yujin, et al.
Published: (2024)
by: Han, Yujin, et al.
Published: (2024)
On the Feature Learning in Diffusion Models
by: Han, Andi, et al.
Published: (2024)
by: Han, Andi, et al.
Published: (2024)
Reverse Diffusion Monte Carlo
by: Huang, Xunpeng, et al.
Published: (2023)
by: Huang, Xunpeng, et al.
Published: (2023)
SIDE: Surrogate Conditional Data Extraction from Diffusion Models
by: Chen, Yunhao, et al.
Published: (2024)
by: Chen, Yunhao, et al.
Published: (2024)
On the Memorization of Consistency Distillation for Diffusion Models
by: Jiang, Bingqing, et al.
Published: (2026)
by: Jiang, Bingqing, et al.
Published: (2026)
Physics-Informed Distillation of Diffusion Models for PDE-Constrained Generation
by: Zhang, Yi, et al.
Published: (2025)
by: Zhang, Yi, et al.
Published: (2025)
Hierarchical Koopman Diffusion: Fast Generation with Interpretable Diffusion Trajectory
by: Bai, Hanru, et al.
Published: (2025)
by: Bai, Hanru, et al.
Published: (2025)
On the Collapse Errors Induced by the Deterministic Sampler for Diffusion Models
by: Zhang, Yi, et al.
Published: (2025)
by: Zhang, Yi, et al.
Published: (2025)
How Does Label Noise Gradient Descent Improve Generalization in the Low SNR Regime?
by: Huang, Wei, et al.
Published: (2025)
by: Huang, Wei, et al.
Published: (2025)
On the Benefits of Over-parameterization for Out-of-Distribution Generalization
by: Hao, Yifan, et al.
Published: (2024)
by: Hao, Yifan, et al.
Published: (2024)
Extracting Training Data from Unconditional Diffusion Models
by: Chen, Yunhao, et al.
Published: (2024)
by: Chen, Yunhao, et al.
Published: (2024)
Slight Corruption in Pre-training Data Makes Better Diffusion Models
by: Chen, Hao, et al.
Published: (2024)
by: Chen, Hao, et al.
Published: (2024)
Hyper-SET: Designing Transformers via Hyperspherical Energy Minimization
by: Hu, Yunzhe, et al.
Published: (2025)
by: Hu, Yunzhe, et al.
Published: (2025)
What Can Transformer Learn with Varying Depth? Case Studies on Sequence Learning Tasks
by: Chen, Xingwu, et al.
Published: (2024)
by: Chen, Xingwu, et al.
Published: (2024)
Physics-Informed Neural PDE Solvers via Spatio-Temporal MeanFlow
by: Bai, Hanru, et al.
Published: (2026)
by: Bai, Hanru, et al.
Published: (2026)
Masked Autoencoders Are Effective Tokenizers for Diffusion Models
by: Chen, Hao, et al.
Published: (2025)
by: Chen, Hao, et al.
Published: (2025)
An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models
by: Hu, Yunzhe, et al.
Published: (2024)
by: Hu, Yunzhe, et al.
Published: (2024)
AIGB: Generative Auto-bidding via Conditional Diffusion Modeling
by: Guo, Jiayan, et al.
Published: (2024)
by: Guo, Jiayan, et al.
Published: (2024)
A Human-Like Reasoning Framework for Multi-Phases Planning Task with Large Language Models
by: Xie, Chengxing, et al.
Published: (2024)
by: Xie, Chengxing, et al.
Published: (2024)
The Implicit Bias of Adam on Separable Data
by: Zhang, Chenyang, et al.
Published: (2024)
by: Zhang, Chenyang, et al.
Published: (2024)
Latent Shadows: The Gaussian-Discrete Duality in Masked Diffusion
by: Chen, Guinan, et al.
Published: (2026)
by: Chen, Guinan, et al.
Published: (2026)
Distilled Decoding 2: One-step Sampling of Image Auto-regressive Models with Conditional Score Distillation
by: Liu, Enshu, et al.
Published: (2025)
by: Liu, Enshu, et al.
Published: (2025)
Structured Role-Aware Policy Optimization for Multimodal Reasoning
by: Jiang, Bingqing, et al.
Published: (2026)
by: Jiang, Bingqing, et al.
Published: (2026)
Controlled LLM Decoding via Discrete Auto-regressive Biasing
by: Pynadath, Patrick, et al.
Published: (2025)
by: Pynadath, Patrick, et al.
Published: (2025)
Understanding the Generalization of Stochastic Gradient Adam in Learning Neural Networks
by: Tang, Xuan, et al.
Published: (2025)
by: Tang, Xuan, et al.
Published: (2025)
Capturing the Temporal Dependence of Training Data Influence
by: Wang, Jiachen T., et al.
Published: (2024)
by: Wang, Jiachen T., et al.
Published: (2024)
DLM-Scope: Mechanistic Interpretability of Diffusion Language Models via Sparse Autoencoders
by: Wang, Xu, et al.
Published: (2026)
by: Wang, Xu, et al.
Published: (2026)
Learning under Quantization for High-Dimensional Linear Regression
by: Zhang, Dechen, et al.
Published: (2025)
by: Zhang, Dechen, et al.
Published: (2025)
How Transformers Utilize Multi-Head Attention in In-Context Learning? A Case Study on Sparse Linear Regression
by: Chen, Xingwu, et al.
Published: (2024)
by: Chen, Xingwu, et al.
Published: (2024)
Improving Implicit Regularization of SGD with Preconditioning for Least Square Problems
by: Su, Junwei, et al.
Published: (2024)
by: Su, Junwei, et al.
Published: (2024)
On the Limitation and Experience Replay for GNNs in Continual Learning
by: Su, Junwei, et al.
Published: (2023)
by: Su, Junwei, et al.
Published: (2023)
The Implicit Bias of Steepest Descent with Mini-batch Stochastic Gradient
by: Li, Jichu, et al.
Published: (2026)
by: Li, Jichu, et al.
Published: (2026)
PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks
by: Su, Junwei, et al.
Published: (2024)
by: Su, Junwei, et al.
Published: (2024)
Similar Items
-
Faster Sampling without Isoperimetry via Diffusion-based Monte Carlo
by: Huang, Xunpeng, et al.
Published: (2024) -
On the $ε$-Free Inference Complexity of Absorbing Discrete Diffusion
by: Huang, Xunpeng, et al.
Published: (2025) -
Almost Linear Convergence under Minimal Score Assumptions: Quantized Transition Diffusion
by: Huang, Xunpeng, et al.
Published: (2025) -
An Improved Analysis of Langevin Algorithms with Prior Diffusion for Non-Log-Concave Sampling
by: Huang, Xunpeng, et al.
Published: (2024) -
Faster Sampling via Stochastic Gradient Proximal Sampler
by: Huang, Xunpeng, et al.
Published: (2024)