Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner
Fuente:
arXiv
Saved in:
| Main Authors: | Zhou, Cai, Yang, Chenxiao, Hu, Yi, Wang, Chenyu, Zhang, Chubin, Zhang, Muhan, Mackey, Lester, Jaakkola, Tommi, Bates, Stephen, Zhang, Dinghuai |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Next Semantic Scale Prediction via Hierarchical Diffusion Language Models
by: Zhou, Cai, et al.
Published: (2025)
by: Zhou, Cai, et al.
Published: (2025)
Learning Diffusion Models with Flexible Representation Guidance
by: Wang, Chenyu, et al.
Published: (2025)
by: Wang, Chenyu, et al.
Published: (2025)
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents
by: Xu, Yilun, et al.
Published: (2024)
by: Xu, Yilun, et al.
Published: (2024)
Rethinking Diffusion Models with Symmetries through Canonicalization with Applications to Molecular Graph Generation
by: Zhou, Cai, et al.
Published: (2026)
by: Zhou, Cai, et al.
Published: (2026)
Thought calibration: Efficient and confident test-time scaling
by: Wu, Menghua, et al.
Published: (2025)
by: Wu, Menghua, et al.
Published: (2025)
Unifying Generation and Prediction on Graphs with Latent Graph Diffusion
by: Zhou, Cai, et al.
Published: (2024)
by: Zhou, Cai, et al.
Published: (2024)
Continuously Tempered Diffusion Samplers
by: Erives, Ezra, et al.
Published: (2025)
by: Erives, Ezra, et al.
Published: (2025)
Correcting Diffusion Generation through Resampling
by: Liu, Yujian, et al.
Published: (2023)
by: Liu, Yujian, et al.
Published: (2023)
Diffusion As Self-Distillation: End-to-End Latent Diffusion In One Model
by: Wang, Xiyuan, et al.
Published: (2025)
by: Wang, Xiyuan, et al.
Published: (2025)
Online Reasoning Calibration: Test-Time Training Enables Generalizable Conformal LLM Reasoning
by: Zhou, Cai, et al.
Published: (2026)
by: Zhou, Cai, et al.
Published: (2026)
What Affects the Effective Depth of Large Language Models?
by: Hu, Yi, et al.
Published: (2025)
by: Hu, Yi, et al.
Published: (2025)
Think While You Generate: Discrete Diffusion with Planned Denoising
by: Liu, Sulin, et al.
Published: (2024)
by: Liu, Sulin, et al.
Published: (2024)
Diffusion Domain Expansion: Learning to Coordinate Pre-trained Diffusion Models
by: Lifar, Egor, et al.
Published: (2026)
by: Lifar, Egor, et al.
Published: (2026)
Informed Correctors for Discrete Diffusion Models
by: Zhao, Yixiu, et al.
Published: (2024)
by: Zhao, Yixiu, et al.
Published: (2024)
Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design
by: Wang, Chenyu, et al.
Published: (2024)
by: Wang, Chenyu, et al.
Published: (2024)
SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models
by: Wang, Chenyu, et al.
Published: (2025)
by: Wang, Chenyu, et al.
Published: (2025)
Continuous Diffusion Scales Competitively with Discrete Diffusion for Language
by: Yang, Zhihan, et al.
Published: (2026)
by: Yang, Zhihan, et al.
Published: (2026)
Diffusion models in protein structure and docking
by: Jason Yim, et al.
Published: (2024)
by: Jason Yim, et al.
Published: (2024)
Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making
by: Feng, Fan, et al.
Published: (2026)
by: Feng, Fan, 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)
by: Tang, Luhan, et al.
Published: (2026)
Diffusion Large Language Models for Black-Box Optimization
by: Yuan, Ye, et al.
Published: (2026)
by: Yuan, Ye, et al.
Published: (2026)
In-Context Symmetries: Self-Supervised Learning through Contextual World Models
by: Gupta, Sharut, et al.
Published: (2024)
by: Gupta, Sharut, et al.
Published: (2024)
Fictitious Synthetic Data Can Improve LLM Factuality via Prerequisite Learning
by: Liu, Yujian, et al.
Published: (2024)
by: Liu, Yujian, et al.
Published: (2024)
Revisiting Who's Harry Potter: Towards Targeted Unlearning from a Causal Intervention Perspective
by: Liu, Yujian, et al.
Published: (2024)
by: Liu, Yujian, et al.
Published: (2024)
Selftok: Discrete Visual Tokens of Autoregression, by Diffusion, and for Reasoning
by: Wang, Bohan, et al.
Published: (2025)
by: Wang, Bohan, et al.
Published: (2025)
TextLDM: Language Modeling with Continuous Latent Diffusion
by: Jiang, Jiaxiu, et al.
Published: (2026)
by: Jiang, Jiaxiu, et al.
Published: (2026)
On Powerful Ways to Generate: Autoregression, Diffusion, and Beyond
by: Yang, Chenxiao, et al.
Published: (2025)
by: Yang, Chenxiao, et al.
Published: (2025)
GLASS Flows: Transition Sampling for Alignment of Flow and Diffusion Models
by: Holderrieth, Peter, et al.
Published: (2025)
by: Holderrieth, Peter, et al.
Published: (2025)
Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design
by: Campbell, Andrew, et al.
Published: (2024)
by: Campbell, Andrew, et al.
Published: (2024)
CANDI: Hybrid Discrete-Continuous Diffusion Models
by: Pynadath, Patrick, et al.
Published: (2025)
by: Pynadath, Patrick, et al.
Published: (2025)
An Information Criterion for Controlled Disentanglement of Multimodal Data
by: Wang, Chenyu, et al.
Published: (2024)
by: Wang, Chenyu, et al.
Published: (2024)
Latent-DARM: Bridging Discrete Diffusion And Autoregressive Models For Reasoning
by: Berrayana, Lina, et al.
Published: (2026)
by: Berrayana, Lina, et al.
Published: (2026)
GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models
by: Feng, Jiarui, et al.
Published: (2025)
by: Feng, Jiarui, et al.
Published: (2025)
Nabla-R2D3: Effective and Efficient 3D Diffusion Alignment with 2D Rewards
by: Liu, Qingming, et al.
Published: (2025)
by: Liu, Qingming, et al.
Published: (2025)
Improving GFlowNets for Text-to-Image Diffusion Alignment
by: Zhang, Dinghuai, et al.
Published: (2024)
by: Zhang, Dinghuai, et al.
Published: (2024)
Latent Shadows: The Gaussian-Discrete Duality in Masked Diffusion
by: Chen, Guinan, et al.
Published: (2026)
by: Chen, Guinan, et al.
Published: (2026)
Continuously Augmented Discrete Diffusion model for Categorical Generative Modeling
by: Zheng, Huangjie, et al.
Published: (2025)
by: Zheng, Huangjie, et al.
Published: (2025)
Continuous Latent Diffusion Language Model
by: Guo, Hongcan, et al.
Published: (2026)
by: Guo, Hongcan, et al.
Published: (2026)
TabDLM: Free-Form Tabular Data Generation via Joint Numerical-Language Diffusion
by: Cai, Donghong, et al.
Published: (2026)
by: Cai, Donghong, et al.
Published: (2026)
Calibrated Selective Classification
by: Fisch, Adam, et al.
Published: (2022)
by: Fisch, Adam, et al.
Published: (2022)
Similar Items
-
Next Semantic Scale Prediction via Hierarchical Diffusion Language Models
by: Zhou, Cai, et al.
Published: (2025) -
Learning Diffusion Models with Flexible Representation Guidance
by: Wang, Chenyu, et al.
Published: (2025) -
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents
by: Xu, Yilun, et al.
Published: (2024) -
Rethinking Diffusion Models with Symmetries through Canonicalization with Applications to Molecular Graph Generation
by: Zhou, Cai, et al.
Published: (2026) -
Thought calibration: Efficient and confident test-time scaling
by: Wu, Menghua, et al.
Published: (2025)