ABC: Any-Subset Autoregression via Non-Markovian Diffusion Bridges in Continuous Time and Space
Fuente:
arXiv
Saved in:
| Main Authors: | Guo, Gabe, Sornwanee, Thanawat, Hao, Lutong, Litman, Elon, Ermon, Stefano, Blanchet, Jose |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Reviving Any-Subset Autoregressive Models with Principled Parallel Sampling and Speculative Decoding
by: Guo, Gabe, et al.
Published: (2025)
by: Guo, Gabe, et al.
Published: (2025)
You Need Better Attention Priors
by: Litman, Elon, et al.
Published: (2026)
by: Litman, Elon, et al.
Published: (2026)
A Theory of Generalization in Deep Learning
by: Litman, Elon, et al.
Published: (2026)
by: Litman, Elon, et al.
Published: (2026)
Unbiased Single-Queried Gradient for Combinatorial Objective
by: Sornwanee, Thanawat
Published: (2026)
by: Sornwanee, Thanawat
Published: (2026)
Differentiable Integer Linear Programming is not Differentiable & it's not a mere technical problem
by: Sornwanee, Thanawat
Published: (2026)
by: Sornwanee, Thanawat
Published: (2026)
1-Dimensional Normal Competitive Market Equilibrium
by: Sornwanee, Thanawat
Published: (2025)
by: Sornwanee, Thanawat
Published: (2025)
LLMs are Overconfident: Evaluating Confidence Interval Calibration with FermiEval
by: Epstein, Elliot L., et al.
Published: (2025)
by: Epstein, Elliot L., et al.
Published: (2025)
Allocate Marginal Reviews to Borderline Papers Using LLM Comparative Ranking
by: Epstein, Elliot L., et al.
Published: (2026)
by: Epstein, Elliot L., et al.
Published: (2026)
The Origin of Edge of Stability
by: Litman, Elon
Published: (2026)
by: Litman, Elon
Published: (2026)
Scaled-Dot-Product Attention as One-Sided Entropic Optimal Transport
by: Litman, Elon
Published: (2025)
by: Litman, Elon
Published: (2025)
Equilibrium Propagation Without Limits
by: Litman, Elon
Published: (2025)
by: Litman, Elon
Published: (2025)
SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking
by: Cundy, Chris, et al.
Published: (2023)
by: Cundy, Chris, et al.
Published: (2023)
Self-Refining Diffusion Samplers: Enabling Parallelization via Parareal Iterations
by: Selvam, Nikil Roashan, et al.
Published: (2024)
by: Selvam, Nikil Roashan, et al.
Published: (2024)
Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation
by: Manvi, Rohin, et al.
Published: (2024)
by: Manvi, Rohin, et al.
Published: (2024)
Training-Free Safe Denoisers for Safe Use of Diffusion Models
by: Kim, Mingyu, et al.
Published: (2025)
by: Kim, Mingyu, et al.
Published: (2025)
Projected Autoregression: Autoregressive Language Generation in Continuous State Space
by: Naparstek, Oshri
Published: (2026)
by: Naparstek, Oshri
Published: (2026)
AR-Omni: A Unified Autoregressive Model for Any-to-Any Generation
by: Cheng, Dongjie, et al.
Published: (2026)
by: Cheng, Dongjie, et al.
Published: (2026)
The Principles of Diffusion Models
by: Lai, Chieh-Hsin, et al.
Published: (2025)
by: Lai, Chieh-Hsin, et al.
Published: (2025)
DEER: Draft with Diffusion, Verify with Autoregressive Models
by: Cheng, Zicong, et al.
Published: (2025)
by: Cheng, Zicong, et al.
Published: (2025)
Any-to-Any Learning in Computational Pathology via Triplet Multimodal Pretraining
by: Sun, Qichen, et al.
Published: (2025)
by: Sun, Qichen, et al.
Published: (2025)
SD-KDE: Score-Debiased Kernel Density Estimation
by: Epstein, Elliot L., et al.
Published: (2025)
by: Epstein, Elliot L., et al.
Published: (2025)
Segment Any Change
by: Zheng, Zhuo, et al.
Published: (2024)
by: Zheng, Zhuo, 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)
Non-Myopic Multi-Objective Bayesian Optimization
by: Belakaria, Syrine, et al.
Published: (2024)
by: Belakaria, Syrine, et al.
Published: (2024)
Preference-Guided Diffusion for Multi-Objective Offline Optimization
by: Annadani, Yashas, et al.
Published: (2025)
by: Annadani, Yashas, et al.
Published: (2025)
Inductive Moment Matching
by: Zhou, Linqi, et al.
Published: (2025)
by: Zhou, Linqi, et al.
Published: (2025)
GUDA: Counterfactual Group-wise Training Data Attribution for Diffusion Models via Unlearning
by: Murata, Naoki, et al.
Published: (2026)
by: Murata, Naoki, et al.
Published: (2026)
Non-Markovian Discrete Diffusion with Causal Language Models
by: Zhang, Yangtian, et al.
Published: (2025)
by: Zhang, Yangtian, et al.
Published: (2025)
GeoAda: Efficiently Finetune Geometric Diffusion Models with Equivariant Adapters
by: Zhao, Wanjia, et al.
Published: (2025)
by: Zhao, Wanjia, et al.
Published: (2025)
TabMDA: Tabular Manifold Data Augmentation for Any Classifier using Transformers with In-context Subsetting
by: Margeloiu, Andrei, et al.
Published: (2024)
by: Margeloiu, Andrei, et al.
Published: (2024)
Test-Time Scaling in Diffusion LLMs via Hidden Semi-Autoregressive Experts
by: Lee, Jihoon, et al.
Published: (2025)
by: Lee, Jihoon, et al.
Published: (2025)
Generative Modeling with Flux Matching
by: Pao-Huang, Peter, et al.
Published: (2026)
by: Pao-Huang, Peter, et al.
Published: (2026)
Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution
by: Wu, Tailin, et al.
Published: (2024)
by: Wu, Tailin, et al.
Published: (2024)
Bridging the Know-Act Gap via Task-Level Autoregressive Reasoning
by: Ahn, Jihyun Janice, et al.
Published: (2026)
by: Ahn, Jihyun Janice, et al.
Published: (2026)
GeoEvolve: Automating Geospatial Model Discovery via Multi-Agent Large Language Models
by: Luo, Peng, et al.
Published: (2025)
by: Luo, Peng, et al.
Published: (2025)
Bridging Dynamics Gaps via Diffusion Schrödinger Bridge for Cross-Domain Reinforcement Learning
by: Zhang, Hanping, et al.
Published: (2026)
by: Zhang, Hanping, et al.
Published: (2026)
On the Scalability of Diffusion-based Text-to-Image Generation
by: Li, Hao, et al.
Published: (2024)
by: Li, Hao, et al.
Published: (2024)
Exploring Diffusion Transformer Designs via Grafting
by: Chandrasegaran, Keshigeyan, et al.
Published: (2025)
by: Chandrasegaran, Keshigeyan, et al.
Published: (2025)
Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion
by: Huang, Xun, et al.
Published: (2025)
by: Huang, Xun, et al.
Published: (2025)
Constructing Non-Markovian Decision Process via History Aggregator
by: Wang, Yongyi, et al.
Published: (2025)
by: Wang, Yongyi, et al.
Published: (2025)
Similar Items
-
Reviving Any-Subset Autoregressive Models with Principled Parallel Sampling and Speculative Decoding
by: Guo, Gabe, et al.
Published: (2025) -
You Need Better Attention Priors
by: Litman, Elon, et al.
Published: (2026) -
A Theory of Generalization in Deep Learning
by: Litman, Elon, et al.
Published: (2026) -
Unbiased Single-Queried Gradient for Combinatorial Objective
by: Sornwanee, Thanawat
Published: (2026) -
Differentiable Integer Linear Programming is not Differentiable & it's not a mere technical problem
by: Sornwanee, Thanawat
Published: (2026)