Saved in:
| Main Authors: | Han, Jiaqi, Wang, Austin, Xu, Minkai, Chu, Wenda, Dang, Meihua, Ye, Haotian, Chen, Huayu, Yue, Yisong, Ermon, Stefano |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.04832 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Divergence Minimization Preference Optimization for Diffusion Model Alignment
by: Li, Binxu, et al.
Published: (2025)
by: Li, Binxu, et al.
Published: (2025)
Inference-Time Scaling of Diffusion Language Models via Trajectory Refinement
by: Dang, Meihua, et al.
Published: (2025)
by: Dang, Meihua, et al.
Published: (2025)
Geometric Trajectory Diffusion Models
by: Han, Jiaqi, et al.
Published: (2024)
by: Han, Jiaqi, et al.
Published: (2024)
Beyond Pairwise Preferences: Listwise Reward-Aware Alignment for Diffusion Models
by: Wang, Austin, et al.
Published: (2026)
by: Wang, Austin, et al.
Published: (2026)
CHORDS: Diffusion Sampling Accelerator with Multi-core Hierarchical ODE Solvers
by: Han, Jiaqi, et al.
Published: (2025)
by: Han, Jiaqi, et al.
Published: (2025)
Split Gibbs Discrete Diffusion Posterior Sampling
by: Chu, Wenda, et al.
Published: (2025)
by: Chu, Wenda, et al.
Published: (2025)
TFG: Unified Training-Free Guidance for Diffusion Models
by: Ye, Haotian, et al.
Published: (2024)
by: Ye, Haotian, et al.
Published: (2024)
RFG: Test-Time Scaling for Diffusion Large Language Model Reasoning with Reward-Free Guidance
by: Chen, Tianlang, et al.
Published: (2025)
by: Chen, Tianlang, et al.
Published: (2025)
$f$-PO: Generalizing Preference Optimization with $f$-divergence Minimization
by: Han, Jiaqi, et al.
Published: (2024)
by: Han, Jiaqi, et al.
Published: (2024)
Personalized Preference Fine-tuning of Diffusion Models
by: Dang, Meihua, et al.
Published: (2025)
by: Dang, Meihua, et al.
Published: (2025)
Ensemble Kalman Diffusion Guidance: A Derivative-free Method for Inverse Problems
by: Zheng, Hongkai, et al.
Published: (2024)
by: Zheng, Hongkai, et al.
Published: (2024)
Principled RL for Diffusion LLMs Emerges from a Sequence-Level Perspective
by: Ou, Jingyang, et al.
Published: (2025)
by: Ou, Jingyang, et al.
Published: (2025)
Adaptive Spectral Feature Forecasting for Diffusion Sampling Acceleration
by: Han, Jiaqi, et al.
Published: (2026)
by: Han, Jiaqi, et al.
Published: (2026)
TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation
by: Shi, Juntong, et al.
Published: (2024)
by: Shi, Juntong, et al.
Published: (2024)
Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs
by: Yang, Ling, et al.
Published: (2024)
by: Yang, Ling, et al.
Published: (2024)
MUDiff: Unified Diffusion for Complete Molecule Generation
by: Hua, Chenqing, et al.
Published: (2023)
by: Hua, Chenqing, et al.
Published: (2023)
Scaling Probabilistic Circuits via Monarch Matrices
by: Zhang, Honghua, et al.
Published: (2025)
by: Zhang, Honghua, et al.
Published: (2025)
RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models
by: Hudovernik, Valter, et al.
Published: (2025)
by: Hudovernik, Valter, et al.
Published: (2025)
End-to-End Autoregressive Image Generation with 1D Semantic Tokenizer
by: Chu, Wenda, et al.
Published: (2026)
by: Chu, Wenda, et al.
Published: (2026)
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution
by: Lou, Aaron, et al.
Published: (2023)
by: Lou, Aaron, et al.
Published: (2023)
Contextualized Diffusion Models for Text-Guided Image and Video Generation
by: Yang, Ling, et al.
Published: (2024)
by: Yang, Ling, et al.
Published: (2024)
Energy-Based Diffusion Language Models for Text Generation
by: Xu, Minkai, et al.
Published: (2024)
by: Xu, Minkai, et al.
Published: (2024)
DiffusionNFT: Online Diffusion Reinforcement with Forward Process
by: Zheng, Kaiwen, et al.
Published: (2025)
by: Zheng, Kaiwen, et al.
Published: (2025)
MADiff: Offline Multi-agent Learning with Diffusion Models
by: Zhu, Zhengbang, et al.
Published: (2023)
by: Zhu, Zhengbang, et al.
Published: (2023)
Equivariant Graph Neural Operator for Modeling 3D Dynamics
by: Xu, Minkai, et al.
Published: (2024)
by: Xu, Minkai, et al.
Published: (2024)
CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion
by: Kazdan, Joshua, et al.
Published: (2024)
by: Kazdan, Joshua, et al.
Published: (2024)
Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics
by: Iyengar, Aniketh, et al.
Published: (2026)
by: Iyengar, Aniketh, et al.
Published: (2026)
Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization
by: Gu, Siyi, et al.
Published: (2024)
by: Gu, Siyi, et al.
Published: (2024)
Data-regularized Reinforcement Learning for Diffusion Models at Scale
by: Ye, Haotian, et al.
Published: (2025)
by: Ye, Haotian, et al.
Published: (2025)
GeoAda: Efficiently Finetune Geometric Diffusion Models with Equivariant Adapters
by: Zhao, Wanjia, et al.
Published: (2025)
by: Zhao, Wanjia, et al.
Published: (2025)
Energy Scaling Laws for Diffusion Models: Quantifying Compute in Image Generation
by: Iyengar, Aniketh, et al.
Published: (2025)
by: Iyengar, Aniketh, et al.
Published: (2025)
Self-Refining Diffusion Samplers: Enabling Parallelization via Parareal Iterations
by: Selvam, Nikil Roashan, et al.
Published: (2024)
by: Selvam, Nikil Roashan, et al.
Published: (2024)
InverseBench: Benchmarking Plug-and-Play Diffusion Priors for Inverse Problems in Physical Sciences
by: Zheng, Hongkai, et al.
Published: (2025)
by: Zheng, Hongkai, et al.
Published: (2025)
Improving Diffusion Language Model Decoding through Joint Search in Generation Order and Token Space
by: Shen, Yangyi, et al.
Published: (2026)
by: Shen, Yangyi, et al.
Published: (2026)
InfoTok: Adaptive Discrete Video Tokenizer via Information-Theoretic Compression
by: Ye, Haotian, et al.
Published: (2025)
by: Ye, Haotian, et al.
Published: (2025)
Steering Generative Models with Experimental Data for Protein Fitness Optimization
by: Yang, Jason, et al.
Published: (2025)
by: Yang, Jason, et al.
Published: (2025)
Data Unlearning in Diffusion Models
by: Alberti, Silas, et al.
Published: (2025)
by: Alberti, Silas, et al.
Published: (2025)
Blade: A Derivative-free Bayesian Inversion Method using Diffusion Priors
by: Zheng, Hongkai, et al.
Published: (2025)
by: Zheng, Hongkai, et al.
Published: (2025)
Practical Bayesian Algorithm Execution via Posterior Sampling
by: Cheng, Chu Xin, et al.
Published: (2024)
by: Cheng, Chu Xin, et al.
Published: (2024)
Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion
by: Kim, Dongjun, et al.
Published: (2023)
by: Kim, Dongjun, et al.
Published: (2023)
Similar Items
-
Divergence Minimization Preference Optimization for Diffusion Model Alignment
by: Li, Binxu, et al.
Published: (2025) -
Inference-Time Scaling of Diffusion Language Models via Trajectory Refinement
by: Dang, Meihua, et al.
Published: (2025) -
Geometric Trajectory Diffusion Models
by: Han, Jiaqi, et al.
Published: (2024) -
Beyond Pairwise Preferences: Listwise Reward-Aware Alignment for Diffusion Models
by: Wang, Austin, et al.
Published: (2026) -
CHORDS: Diffusion Sampling Accelerator with Multi-core Hierarchical ODE Solvers
by: Han, Jiaqi, et al.
Published: (2025)