Cover Image

Autoregressive Models Rival Diffusion Models at ANY-ORDER Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Du, Tianqi, Fang, Lizhe, Yang, Weijie, Zhang, Chenheng, Wei, Zeming, Wang, Yifei, Wang, Yisen
Format:	Preprint
Published:	2026
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Language Ranker: A Lightweight Ranking framework for LLM Decoding
by: Zhang, Chenheng, et al.
Published: (2025)

Rethinking Invariance in In-context Learning
by: Fang, Lizhe, et al.
Published: (2025)

Advancing LLM Safe Alignment with Safety Representation Ranking
by: Du, Tianqi, et al.
Published: (2025)

Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations
by: Wei, Zeming, et al.
Published: (2023)

When More is Less: Understanding Chain-of-Thought Length in LLMs
by: Wu, Yuyang, et al.
Published: (2025)

What is Wrong with Perplexity for Long-context Language Modeling?
by: Fang, Lizhe, et al.
Published: (2024)

Fight Back Against Jailbreaking via Prompt Adversarial Tuning
by: Mo, Yichuan, et al.
Published: (2024)

Scalable Defense against In-the-wild Jailbreaking Attacks with Safety Context Retrieval
by: Chen, Taiye, et al.
Published: (2025)

Differences in Text Generated by Diffusion and Autoregressive Language Models
by: Zhang, Zeyang, et al.
Published: (2026)

Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining
by: Zhang, Qi, et al.
Published: (2024)

Are Smarter LLMs Safer? Exploring Safety-Reasoning Trade-offs in Prompting and Fine-Tuning
by: Li, Ang, et al.
Published: (2025)

TrustLDM: Benchmarking Trustworthiness in Language Diffusion Models
by: Mo, Yichuan, et al.
Published: (2026)

DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation
by: Jia, Dongya, et al.
Published: (2025)

Rethinking Personalization in Large Language Models at the Token Level
by: Zhang, Chenheng, et al.
Published: (2026)

ALPINE: Unveiling the Planning Capability of Autoregressive Learning in Language Models
by: Wang, Siwei, et al.
Published: (2024)

Long-Short Alignment for Effective Long-Context Modeling in LLMs
by: Du, Tianqi, et al.
Published: (2025)

RecycleGPT: An Autoregressive Language Model with Recyclable Module
by: Jiang, Yufan, et al.
Published: (2023)

Analyzing Diffusion and Autoregressive Vision Language Models in Multimodal Embedding Space
by: Wang, Zihang, et al.
Published: (2026)

Pipelined Biomedical Event Extraction Rivaling Joint Learning
by: Wu, Pengchao, et al.
Published: (2024)

LaDiC: Are Diffusion Models Really Inferior to Autoregressive Counterparts for Image-to-Text Generation?
by: Wang, Yuchi, et al.
Published: (2024)

Why Diffusion Language Models Struggle with Truly Parallel (Non-Autoregressive) Decoding?
by: Li, Pengxiang, et al.
Published: (2026)

Planner and Executor: Collaboration between Discrete Diffusion And Autoregressive Models in Reasoning
by: Berrayana, Lina, et al.
Published: (2025)

Hierarchical Retrieval-Augmented Generation Model with Rethink for Multi-hop Question Answering
by: Zhang, Xiaoming, et al.
Published: (2024)

Advancing Sequential Numerical Prediction in Autoregressive Models
by: Fei, Xiang, et al.
Published: (2025)

ToolSpectrum : Towards Personalized Tool Utilization for Large Language Models
by: Cheng, Zihao, et al.
Published: (2025)

ReFusion: A Diffusion Large Language Model with Parallel Autoregressive Decoding
by: Li, Jia-Nan, et al.
Published: (2025)

PARAMANU-GANITA: Can Small Math Language Models Rival with Large Language Models on Mathematical Reasoning?
by: Niyogi, Mitodru, et al.
Published: (2024)

AR-Omni: A Unified Autoregressive Model for Any-to-Any Generation
by: Cheng, Dongjie, et al.
Published: (2026)

Adversarial Representation Engineering: A General Model Editing Framework for Large Language Models
by: Zhang, Yihao, et al.
Published: (2024)

Hierarchical Skip Decoding for Efficient Autoregressive Text Generation
by: Zhu, Yunqi, et al.
Published: (2024)

Finding and Reactivating Post-Trained LLMs' Hidden Safety Mechanisms
by: Li, Mingjie, et al.
Published: (2026)

TiDAR: Think in Diffusion, Talk in Autoregression
by: Liu, Jingyu, et al.
Published: (2025)

Defending Large Language Models Against Jailbreak Attacks via In-Decoding Safety-Awareness Probing
by: Zhao, Yinzhi, et al.
Published: (2026)

Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed
by: Fu, Yonggan, et al.
Published: (2025)

Language Models as Continuous Self-Evolving Data Engineers
by: Wang, Peidong, et al.
Published: (2024)

Generative AI Purpose-built for Social and Mental Health: A Real-World Pilot
by: Hull, Thomas D., et al.
Published: (2025)

CIRAG: Construction-Integration Retrieval and Adaptive Generation for Multi-hop Question Answering
by: Wei, Zili, et al.
Published: (2026)

PatchWorld: Gradient-Free Optimization of Executable World Models
by: Bai, Jiaxin, et al.
Published: (2026)

Automata-Based Steering of Large Language Models for Diverse Structured Generation
by: Luan, Xiaokun, et al.
Published: (2025)

2M-NER: Contrastive Learning for Multilingual and Multimodal NER with Language and Modal Fusion
by: Wang, Dongsheng, et al.
Published: (2024)