Copertina

AI4BayesCode: From Natural Language Descriptions to Validated Modular Stateful Bayesian Samplers

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zou, Jungang, Jiang, Alex Ziyu, Chen, Qixuan
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computation Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

On the Collapse Errors Induced by the Deterministic Sampler for Diffusion Models
di: Zhang, Yi, et al.
Pubblicazione: (2025)

Swift Sampler: Efficient Learning of Sampler by 10 Parameters
di: Yao, Jiawei, et al.
Pubblicazione: (2024)

Proximal Diffusion Neural Sampler
di: Guo, Wei, et al.
Pubblicazione: (2025)

MoBayes: A Modular Bayesian Framework for Separating Reasoning from Language in Conversational Clinical Decision Support
di: Kesmen, Yusuf, et al.
Pubblicazione: (2026)

On Subjective Uncertainty Quantification and Calibration in Natural Language Generation
di: Wang, Ziyu, et al.
Pubblicazione: (2024)

Non-equilibrium Annealed Adjoint Sampler
di: Choi, Jaemoo, et al.
Pubblicazione: (2025)

Continuously Tempered Diffusion Samplers
di: Erives, Ezra, et al.
Pubblicazione: (2025)

ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization
di: Chen, Shengzhuang, et al.
Pubblicazione: (2025)

Rethinking Losses for Diffusion Bridge Samplers
di: Sanokowski, Sebastian, et al.
Pubblicazione: (2025)

Bayesian Predictive Coding
di: Tschantz, Alexander, et al.
Pubblicazione: (2025)

DAFOS: Dynamic Adaptive Fanout Optimization Sampler
di: Ullah, Irfan, et al.
Pubblicazione: (2025)

Decoding as Optimisation on the Probability Simplex: From Top-K to Top-P (Nucleus) to Best-of-K Samplers
di: Ji, Xiaotong, et al.
Pubblicazione: (2026)

Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints
di: Kong, Lingkai, et al.
Pubblicazione: (2024)

LILO: Bayesian Optimization with Natural Language Feedback
di: Kobalczyk, Katarzyna, et al.
Pubblicazione: (2025)

Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
di: Havens, Aaron, et al.
Pubblicazione: (2025)

Natural Language Reinforcement Learning
di: Feng, Xidong, et al.
Pubblicazione: (2024)

Conditional Synthesis of 3D Molecules with Time Correction Sampler
di: Jung, Hojung, et al.
Pubblicazione: (2024)

End-To-End Learning of Gaussian Mixture Priors for Diffusion Sampler
di: Blessing, Denis, et al.
Pubblicazione: (2025)

AIDE: AI-Driven Exploration in the Space of Code
di: Jiang, Zhengyao, et al.
Pubblicazione: (2025)

Natural Language Reinforcement Learning
di: Feng, Xidong, et al.
Pubblicazione: (2024)

BONSAI: Bayesian Optimization with Natural Simplicity and Interpretability
di: Daulton, Samuel, et al.
Pubblicazione: (2026)

Self-Refining Diffusion Samplers: Enabling Parallelization via Parareal Iterations
di: Selvam, Nikil Roashan, et al.
Pubblicazione: (2024)

Nature Language Model: Deciphering the Language of Nature for Scientific Discovery
di: Xia, Yingce, et al.
Pubblicazione: (2025)

Understanding Sampler Stochasticity in Training Diffusion Models for RLHF
di: Sheng, Jiayuan, et al.
Pubblicazione: (2025)

Unlocking Emergent Modularity in Large Language Models
di: Qiu, Zihan, et al.
Pubblicazione: (2023)

AI-Driven Prognostics for State of Health Prediction in Li-ion Batteries: A Comprehensive Analysis with Validation
di: Ding, Tianqi, et al.
Pubblicazione: (2025)

Chemical Language Models for Natural Products: A State-Space Model Approach
di: Wang, Ho-Hsuan, et al.
Pubblicazione: (2026)

A priori Estimates for Deep Residual Network in Continuous-time Reinforcement Learning
di: Yin, Shuyu, et al.
Pubblicazione: (2024)

Damper-B-PINN: Damper Characteristics-Based Bayesian Physics-Informed Neural Network for Vehicle State Estimation
di: Zeng, Tianyi, et al.
Pubblicazione: (2025)

Bayesian Flow Networks
di: Graves, Alex, et al.
Pubblicazione: (2023)

TRISKELION-1: Unified Descriptive-Predictive-Generative AI
di: Kumar, Nardeep, et al.
Pubblicazione: (2025)

Modular Machine Learning: An Indispensable Path towards New-Generation Large Language Models
di: Wang, Xin, et al.
Pubblicazione: (2025)

Planning In Natural Language Improves LLM Search For Code Generation
di: Wang, Evan, et al.
Pubblicazione: (2024)

Multiple Kronecker RLS fusion-based link propagation for drug-side effect prediction
di: Qian, Yuqing, et al.
Pubblicazione: (2024)

Position: agentic AI orchestration should be Bayes-consistent
di: Papamarkou, Theodore, et al.
Pubblicazione: (2026)

tBayes-MICE: A Bayesian Approach to Multiple Imputation for Time Series Data
di: Ibenegbu, Amuche, et al.
Pubblicazione: (2026)

Can Active Label Correction Improve LLM-based Modular AI Systems?
di: Taneja, Karan, et al.
Pubblicazione: (2024)

Efficient Triple Modular Redundancy for Reliability Enhancement of DNNs Using Explainable AI
di: Soroush, Kimia, et al.
Pubblicazione: (2025)

Composition of Experts: A Modular Compound AI System Leveraging Large Language Models
di: Jain, Swayambhoo, et al.
Pubblicazione: (2024)

A Survey of the State of Explainable AI for Natural Language Processing
di: Danilevsky, Marina, et al.
Pubblicazione: (2020)