Cover Image

NI Sampling: Accelerating Discrete Diffusion Sampling by Token Order Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Enshu, Ning, Xuefei, Wang, Yu, Lin, Zinan
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching
by: Liu, Enshu, et al.
Published: (2024)

Distilled Decoding 2: One-step Sampling of Image Auto-regressive Models with Conditional Score Distillation
by: Liu, Enshu, et al.
Published: (2025)

Latent Zoning Network: A Unified Principle for Generative Modeling, Representation Learning, and Classification
by: Lin, Zinan, et al.
Published: (2025)

Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs
by: Liu, Enshu, et al.
Published: (2024)

Accelerating Parallel Sampling of Diffusion Models
by: Tang, Zhiwei, et al.
Published: (2024)

Accelerating Diffusion Sampling with Optimized Time Steps
by: Xue, Shuchen, et al.
Published: (2024)

Discrete Diffusion with Sample-Efficient Estimators for Conditionals
by: Elamvazhuthi, Karthik, et al.
Published: (2026)

Improved Sampling Schedules for Discrete Diffusion Models
by: Foresti, Alberto, et al.
Published: (2026)

Loopholing Discrete Diffusion: Deterministic Bypass of the Sampling Wall
by: Jo, Mingyu, et al.
Published: (2025)

Accelerated Diffusion Models via Speculative Sampling
by: De Bortoli, Valentin, et al.
Published: (2025)

Token Pruning for Caching Better: 9 Times Acceleration on Stable Diffusion for Free
by: Zhang, Evelyn, et al.
Published: (2024)

Alternating Diffusion for Proximal Sampling with Zeroth Order Queries
by: Takagi, Hirohane, et al.
Published: (2026)

DDPS: Discrete Diffusion Posterior Sampling for Paths in Layered Graphs
by: Luan, Hao, et al.
Published: (2025)

Universally Empowering Zeroth-Order Optimization via Adaptive Layer-wise Sampling
by: Wang, Fei, et al.
Published: (2026)

Split Gibbs Discrete Diffusion Posterior Sampling
by: Chu, Wenda, et al.
Published: (2025)

Token Sample Complexity of Attention
by: Bohbot, Léa, et al.
Published: (2025)

Reheated Gradient-based Discrete Sampling for Combinatorial Optimization
by: Li, Muheng, et al.
Published: (2025)

Preference Optimization with Multi-Sample Comparisons
by: Wang, Chaoqi, et al.
Published: (2024)

Optimized Speculative Sampling for GPU Hardware Accelerators
by: Wagner, Dominik, et al.
Published: (2024)

Discrete State Diffusion Models: A Sample Complexity Perspective
by: Srikanth, Aadithya, et al.
Published: (2025)

Test-Time Anchoring for Discrete Diffusion Posterior Sampling
by: Rout, Litu, et al.
Published: (2025)

CHORDS: Diffusion Sampling Accelerator with Multi-core Hierarchical ODE Solvers
by: Han, Jiaqi, et al.
Published: (2025)

Rethinking Importance Sampling in LLM Policy Optimization: A Cumulative Token Perspective
by: Zhang, Yuheng, et al.
Published: (2026)

Kernel Learning for Sample Constrained Black-Box Optimization
by: Rajagopalan, Rajalaxmi, et al.
Published: (2025)

Implicit Diffusion: Efficient Optimization through Stochastic Sampling
by: Marion, Pierre, et al.
Published: (2024)

Window-Diffusion: Accelerating Diffusion Language Model Inference with Windowed Token Pruning and Caching
by: Zuo, Fengrui, et al.
Published: (2026)

Risk-Sensitive Diffusion: Robustly Optimizing Diffusion Models with Noisy Samples
by: Li, Yangming, et al.
Published: (2024)

Double Descent as a Lens for Sample Efficiency in Autoregressive vs. Discrete Diffusion Models
by: Fraij, Ahmad, et al.
Published: (2025)

A Sample Efficient Conditional Independence Test in the Presence of Discretization
by: Sun, Boyang, et al.
Published: (2025)

Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees
by: Dmitriev, Daniil, et al.
Published: (2026)

Accelerated Sampling from Masked Diffusion Models via Entropy Bounded Unmasking
by: Ben-Hamu, Heli, et al.
Published: (2025)

$\textit{Jump Your Steps}$: Optimizing Sampling Schedule of Discrete Diffusion Models
by: Park, Yong-Hyun, et al.
Published: (2024)

SFBD Flow: A Continuous-Optimization Framework for Training Diffusion Models with Noisy Samples
by: Lu, Haoye, et al.
Published: (2025)

Adaptive Spectral Feature Forecasting for Diffusion Sampling Acceleration
by: Han, Jiaqi, et al.
Published: (2026)

Variance-Reduction Guidance: Sampling Trajectory Optimization for Diffusion Models
by: Xu, Shifeng, et al.
Published: (2025)

Discrete Bayesian Sample Inference for Graph Generation
by: Petersen, Ole, et al.
Published: (2025)

GIPO: Gaussian Importance Sampling Policy Optimization
by: Lu, Chengxuan, et al.
Published: (2026)

T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching
by: Pan, Zizheng, et al.
Published: (2024)

Conditional Diffusion Sampling
by: Castro-Macías, Francisco M., et al.
Published: (2026)

Diffusion Rejection Sampling
by: Na, Byeonghu, et al.
Published: (2024)