Saved in:
| Main Authors: | Batzolis, Georgios, Girolami, Mark, Ambrogioni, Luca |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.07013 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Language Diffusion Models are Associative Memories Capable of Retrieving Unseen Data
by: Pham, Bao, et al.
Published: (2026)
by: Pham, Bao, et al.
Published: (2026)
Noise Scheduling as Information-Guided Allocation in Diffusion Training
by: Raya, Gabriel, et al.
Published: (2026)
by: Raya, Gabriel, et al.
Published: (2026)
BitBypass: A New Direction in Jailbreaking Aligned Large Language Models with Bitstream Camouflage
by: Nakka, Kalyan, et al.
Published: (2025)
by: Nakka, Kalyan, et al.
Published: (2025)
Causal Autoregressive Diffusion Language Model
by: Ruan, Junhao, et al.
Published: (2026)
by: Ruan, Junhao, et al.
Published: (2026)
Scaling Diffusion Language Models via Adaptation from Autoregressive Models
by: Gong, Shansan, et al.
Published: (2024)
by: Gong, Shansan, et al.
Published: (2024)
Continuous Autoregressive Language Models
by: Shao, Chenze, et al.
Published: (2025)
by: Shao, Chenze, et al.
Published: (2025)
MixCE: Training Autoregressive Language Models by Mixing Forward and Reverse Cross-Entropies
by: Zhang, Shiyue, et al.
Published: (2023)
by: Zhang, Shiyue, et al.
Published: (2023)
CAWN: Continuous Acoustic Wave Networks for Autoregressive Language Modeling
by: Čugalj, Dejan, et al.
Published: (2026)
by: Čugalj, Dejan, et al.
Published: (2026)
Entropy-Guided Token Dropout: Training Autoregressive Language Models with Limited Domain Data
by: Wang, Jiapeng, et al.
Published: (2025)
by: Wang, Jiapeng, et al.
Published: (2025)
Closing the Confidence-Faithfulness Gap in Large Language Models
by: Miao, Miranda Muqing, et al.
Published: (2026)
by: Miao, Miranda Muqing, et al.
Published: (2026)
Differences in Text Generated by Diffusion and Autoregressive Language Models
by: Zhang, Zeyang, et al.
Published: (2026)
by: Zhang, Zeyang, et al.
Published: (2026)
LangGap: Diagnosing and Closing the Language Gap in Vision-Language-Action Models
by: Hou, Yuchen, et al.
Published: (2026)
by: Hou, Yuchen, et al.
Published: (2026)
Autoregressive vs. Masked Diffusion Language Models: A Controlled Comparison
by: Vicentino, Caio
Published: (2026)
by: Vicentino, Caio
Published: (2026)
Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective
by: Zhang, Siyue, et al.
Published: (2025)
by: Zhang, Siyue, et al.
Published: (2025)
AR-MAP: Are Autoregressive Large Language Models Implicit Teachers for Diffusion Large Language Models?
by: Lin, Liang, et al.
Published: (2026)
by: Lin, Liang, et al.
Published: (2026)
FourierSampler: Unlocking Non-Autoregressive Potential in Diffusion Language Models via Frequency-Guided Generation
by: He, Siyang, et al.
Published: (2026)
by: He, Siyang, et al.
Published: (2026)
How Out-of-Equilibrium Phase Transitions can Seed Pattern Formation in Trained Diffusion Models
by: Ambrogioni, Luca
Published: (2026)
by: Ambrogioni, Luca
Published: (2026)
Projected Autoregression: Autoregressive Language Generation in Continuous State Space
by: Naparstek, Oshri
Published: (2026)
by: Naparstek, Oshri
Published: (2026)
Blockwise SFT for Diffusion Language Models: Reconciling Bidirectional Attention and Autoregressive Decoding
by: Sun, Bowen, et al.
Published: (2025)
by: Sun, Bowen, et al.
Published: (2025)
EntropyCache: Decoded Token Entropy Guided KV Caching for Diffusion Language Models
by: Cheong, Minsoo, et al.
Published: (2026)
by: Cheong, Minsoo, et al.
Published: (2026)
Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows
by: Zhang, Ruixiang, et al.
Published: (2025)
by: Zhang, Ruixiang, et al.
Published: (2025)
Closing the Modality Reasoning Gap for Speech Large Language Models
by: Wang, Chaoren, et al.
Published: (2026)
by: Wang, Chaoren, et al.
Published: (2026)
Masked Diffusion Language Models with Frequency-Informed Training
by: Kosmopoulou, Despoina, et al.
Published: (2025)
by: Kosmopoulou, Despoina, et al.
Published: (2025)
GateKD: Confidence-Gated Closed-Loop Distillation for Robust Reasoning
by: Sermsri, Kasidit, et al.
Published: (2026)
by: Sermsri, Kasidit, et al.
Published: (2026)
Gated Integration of Low-Rank Adaptation for Continual Learning of Large Language Models
by: Liang, Yan-Shuo, et al.
Published: (2025)
by: Liang, Yan-Shuo, et al.
Published: (2025)
Reversal Invariance in Autoregressive Language Models
by: Sahasrabudhe, Mihir
Published: (2025)
by: Sahasrabudhe, Mihir
Published: (2025)
Why Diffusion Language Models Struggle with Truly Parallel (Non-Autoregressive) Decoding?
by: Li, Pengxiang, et al.
Published: (2026)
by: Li, Pengxiang, et al.
Published: (2026)
Analyzing Diffusion and Autoregressive Vision Language Models in Multimodal Embedding Space
by: Wang, Zihang, et al.
Published: (2026)
by: Wang, Zihang, et al.
Published: (2026)
Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed
by: Fu, Yonggan, et al.
Published: (2025)
by: Fu, Yonggan, et al.
Published: (2025)
LARFT: Closing the Cognition-Action Gap for Length Instruction Following in Large Language Models
by: Zhang, Wei, et al.
Published: (2026)
by: Zhang, Wei, et al.
Published: (2026)
Detoxifying Large Language Models via Autoregressive Reward Guided Representation Editing
by: Xiao, Yisong, et al.
Published: (2025)
by: Xiao, Yisong, et al.
Published: (2025)
Bridging the Discrete-Continuous Gap: Unified Multimodal Generation via Coupled Manifold Discrete Absorbing Diffusion
by: Xu, Yuanfeng, et al.
Published: (2026)
by: Xu, Yuanfeng, et al.
Published: (2026)
Revisiting Knowledge Distillation for Autoregressive Language Models
by: Zhong, Qihuang, et al.
Published: (2024)
by: Zhong, Qihuang, et al.
Published: (2024)
Autoregressive Large Language Models are Computationally Universal
by: Schuurmans, Dale, et al.
Published: (2024)
by: Schuurmans, Dale, et al.
Published: (2024)
Swordsman: Entropy-Driven Adaptive Block Partition for Efficient Diffusion Language Models
by: Zhang, Yu, et al.
Published: (2026)
by: Zhang, Yu, et al.
Published: (2026)
ReFusion: A Diffusion Large Language Model with Parallel Autoregressive Decoding
by: Li, Jia-Nan, et al.
Published: (2025)
by: Li, Jia-Nan, et al.
Published: (2025)
Autoregressive Models Rival Diffusion Models at ANY-ORDER Generation
by: Du, Tianqi, et al.
Published: (2026)
by: Du, Tianqi, et al.
Published: (2026)
Blind Bitstream-corrupted Video Recovery via Metadata-guided Diffusion Model
by: Wang, Shuyun, et al.
Published: (2026)
by: Wang, Shuyun, et al.
Published: (2026)
Towards the Law of Capacity Gap in Distilling Language Models
by: Zhang, Chen, et al.
Published: (2023)
by: Zhang, Chen, et al.
Published: (2023)
TextLDM: Language Modeling with Continuous Latent Diffusion
by: Jiang, Jiaxiu, et al.
Published: (2026)
by: Jiang, Jiaxiu, et al.
Published: (2026)
Similar Items
-
Language Diffusion Models are Associative Memories Capable of Retrieving Unseen Data
by: Pham, Bao, et al.
Published: (2026) -
Noise Scheduling as Information-Guided Allocation in Diffusion Training
by: Raya, Gabriel, et al.
Published: (2026) -
BitBypass: A New Direction in Jailbreaking Aligned Large Language Models with Bitstream Camouflage
by: Nakka, Kalyan, et al.
Published: (2025) -
Causal Autoregressive Diffusion Language Model
by: Ruan, Junhao, et al.
Published: (2026) -
Scaling Diffusion Language Models via Adaptation from Autoregressive Models
by: Gong, Shansan, et al.
Published: (2024)