Cover Image

Discrete Stochastic Localization for Non-autoregressive Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Yunshu, Cheng, Jiayi, Yu, Longxuan, Thakuria, Partha, Brekelmans, Rob, Papalexakis, Evangelos E., Steeg, Greg Ver
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Discrete Stochastic Localization for Non-autoregressive Generation
by: Wu, Yunshu, et al.
Published: (2026)

Measurement-Aligned Sampling for Inverse Problem
by: Zhang, Shaorong, et al.
Published: (2025)

Generation Order and Parallel Decoding in Masked Diffusion Models: An Information-Theoretic Perspective
by: Zhang, Shaorong, et al.
Published: (2026)

Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive Training
by: Wu, Yunshu, et al.
Published: (2024)

Spectral Regularization for Diffusion Models
by: Chandran, Satish, et al.
Published: (2026)

DSL-LLaDA: Scaling Continuous Denoising to 8B Masked Diffusion LMs
by: Yu, Longxuan, et al.
Published: (2026)

Is Your Diffusion Sampler Actually Correct? A Sampler-Centric Evaluation of Discrete Diffusion Language Models
by: Tang, Luhan, et al.
Published: (2026)

Local MAP Sampling for Diffusion Models
by: Zhang, Shaorong, et al.
Published: (2025)

Improving Mutual Information Estimation with Annealed and Energy-Based Bounds
by: Brekelmans, Rob, et al.
Published: (2023)

MMG: Mutual Information Estimation via the MMSE Gap in Diffusion
by: Yu, Longxuan, et al.
Published: (2025)

Annealed Importance Sampling with q-Paths
by: Brekelmans, Rob, et al.
Published: (2020)

Exploring the Design Space of Diffusion Bridge Models
by: Zhang, Shaorong, et al.
Published: (2024)

Beyond ROUGE: N-Gram Subspace Features for LLM Hallucination Detection
by: Li, Jerry, et al.
Published: (2025)

Prompt Perturbation Consistency Learning for Robust Language Models
by: Qiang, Yao, et al.
Published: (2024)

Revise, Don't Freeze: Sampler-Matched Training for Self-Correcting Masked Diffusion Language Models
by: Yu, Longxuan, et al.
Published: (2026)

Making Sense Of Distributed Representations With Activation Spectroscopy
by: Reing, Kyle, et al.
Published: (2025)

Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks
by: Shahgir, Haz Sameen, et al.
Published: (2023)

Global and Local Structure Learning for Sparse Tensor Completion
by: Ahn, Dawon, et al.
Published: (2025)

QuAILoRA: Quantization-Aware Initialization for LoRA
by: Lawton, Neal, et al.
Published: (2024)

Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo
by: Zhao, Stephen, et al.
Published: (2024)

Reducing the Probability of Undesirable Outputs in Language Models Using Probabilistic Inference
by: Zhao, Stephen, et al.
Published: (2025)

Thinking Out of Order: When Output Order Stops Reflecting Reasoning Order in Diffusion Language Models
by: Yu, Longxuan, et al.
Published: (2026)

Learning Morphisms with Gauss-Newton Approximation for Growing Networks
by: Lawton, Neal, et al.
Published: (2024)

FedDAPL: Toward Client-Private Generalization in Federated Learning
by: Loaliyan, Soroosh Safari, et al.
Published: (2025)

Scaling the Vocabulary of Non-autoregressive Models for Efficient Generative Retrieval
by: Valluri, Ravisri, et al.
Published: (2024)

Every Response Counts: Quantifying Uncertainty of LLM-based Multi-Agent Systems through Tensor Decomposition
by: Chen, Tiejin, et al.
Published: (2026)

Can a Large Language Model Learn Matrix Functions In Context?
by: Goulart, Paimon, et al.
Published: (2024)

FRAPPE: $\underline{\text{F}}$ast $\underline{\text{Ra}}$nk $\underline{\text{App}}$roximation with $\underline{\text{E}}$xplainable Features for Tensors
by: Shiao, William, et al.
Published: (2022)

A Preliminary Agentic Framework for Matrix Deflation
by: Goulart, Paimon, et al.
Published: (2026)

Variational Representations of Annealing Paths: Bregman Information under Monotonic Embedding
by: Brekelmans, Rob, et al.
Published: (2022)

Interpretable Diffusion via Information Decomposition
by: Kong, Xianghao, et al.
Published: (2023)

Efficiently Generating Multidimensional Calorimeter Data with Tensor Decomposition Parameterization
by: Goulart, Paimon, et al.
Published: (2025)

Multi-View Spectral Clustering for Graphs with Multiple View Structures
by: Tsitsikas, Yorgos, et al.
Published: (2025)

Are LLM Uncertainty and Correctness Encoded by the Same Features? A Functional Dissociation via Sparse Autoencoders
by: Patel, Het, et al.
Published: (2026)

Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding
by: Achille, Alessandro, et al.
Published: (2024)

KG-LLM-Bench: A Scalable Benchmark for Evaluating LLM Reasoning on Textualized Knowledge Graphs
by: Markowitz, Elan, et al.
Published: (2025)

Non-autoregressive Personalized Bundle Generation
by: Yang, Wenchuan, et al.
Published: (2024)

Coeditor: Leveraging Contextual Changes for Multi-round Code Auto-editing
by: Wei, Jiayi, et al.
Published: (2023)

Knowledge Enhanced Multi-Domain Recommendations in an AI Assistant Application
by: Markowitz, Elan, et al.
Published: (2023)

ESI: Epistemic Uncertainty Quantification via Semantic-preserving Intervention for Large Language Models
by: Li, Mingda, et al.
Published: (2025)