arXiv AI August 3, 2026 By Jungang Zou, Alex Ziyu Jiang, Qixuan Chen

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

arXiv:2605. 18476v2 Announce Type: replace-cross Abstract: Coding and computation remain major bottlenecks in Markov chain Monte Carlo (MCMC) workflows, especially as modern sampling algorithms have become increasingly complex and existing probabilistic programming systems remain limited in model support, extensibility, and composability.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv Machine Learning

Jun 18

Structured Inference with Large Language Gibbs

arXiv:2606. 19264v1 Announce Type: new Abstract: The knowledge encoded in large language models (LLMs) can serve as a substrate for structured reasoning over variables describing a complex world, but accessing this knowledge in a probabilistically coherent manner poses a difficult inference problem.

By Sanghyeok Choi, Henry Gouk, Esmeralda S. Whitammer

llms

arXiv Machine Learning

Aug 4

Agentic Bayesian Optimization through Surrogate-Augmented Autoresearch

arXiv:2608. 00316v1 Announce Type: new Abstract: Bayesian optimization (BO) has become the standard tool for sample-efficient optimization and owes its efficiency to uncertainty-aware search driven by generic statistical priors.

By Paul Brunzema, Louis Tiao, Nhat Le, Kevin De Angeli, Yao Xuan, Djordje Gligorijevic

llms agents benchmarks

arXiv AI

Jul 28

Generative Artificial Intelligence (GenAI) to convert images of queuing networks into verifiable simulation models: an open-weight LLM workflow approach

arXiv:2607. 24259v1 Announce Type: new Abstract: Recent work has explored the use of Large Language Models (LLMs) to automate simulation model building, typically by generating executable code directly from natural language descriptions.

By Thomas Monks, Alison Harper, Amy Heather, Navonil Mustafee

llms multimodal benchmarks

arXiv AI

Jul 22

FindStatBench: Evaluating Large Language Models on Combinatorial Code Synthesis

arXiv:2607. 18260v1 Announce Type: new Abstract: We introduce FindStatBench, an execution benchmark for evaluating large language models on combinatorial code synthesis.

By Soham Dan

llms rag agents benchmarks

arXiv Machine Learning

Jul 28

Verbalized Particle Posterior: Bayesian Inference over Natural Language Hypotheses

arXiv:2607. 22961v1 Announce Type: new Abstract: Verbalized Machine Learning (VML) parameterizes a model as a natural-language prompt that an LLM evaluates as f(x; theta).

By Yan Zhang, Shikan Lian, Shibo Li

llms benchmarks

arXiv Machine Learning

Jun 11

LatticeBridge: Rare-Event Sequential Inference for Faithful Structured Sequence Synthesis

arXiv:2606. 11203v1 Announce Type: cross Abstract: Structured sequence generation often requires a model to satisfy several input-derived constraints in a single output.

By Faruk Alpay, Bugra Kilictas

llms benchmarks

Related stories

Structured Inference with Large Language Gibbs

Agentic Bayesian Optimization through Surrogate-Augmented Autoresearch

Generative Artificial Intelligence (GenAI) to convert images of queuing networks into verifiable simulation models: an open-weight LLM workflow approach

FindStatBench: Evaluating Large Language Models on Combinatorial Code Synthesis

Verbalized Particle Posterior: Bayesian Inference over Natural Language Hypotheses

LatticeBridge: Rare-Event Sequential Inference for Faithful Structured Sequence Synthesis