arXiv Machine Learning July 14, 2026 By Bingteng Sun, Hao Yin, Yiling Chen, Renjie Xiao, Lei Xie, Shanyou Wang, Ruonan Wang, Shubao Chen, Qingzong Xu, Lin Lu, Qiang Du, Junqiang Zhu

A Multi-Agent Framework for Zero-Dimensional Reduced-Order Model Planning

Read the original on arXiv Machine Learning →

arXiv:2607. 10994v1 Announce Type: new Abstract: Zero-dimensional reduced-order models (0D ROMs) are central to multi-dimensional design workflows for high-end complex equipment.

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

arXiv Machine Learning

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Learning-based Directed Graph Abstraction of Combinatorial Spaces for Order-Preserving Search in Mixed-Combinatorial Nonlinear Optimization

arXiv:2606. 01425v1 Announce Type: new Abstract: Mixed-combinatorial nonlinear programming (MCNLP) problems arise in many engineering design and planning applications, e.

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arXiv AI

Jun 8

DuMate-DeepResearch: An Auditable Multi-Agent System with Recursive Search and Rubric-Grounded Reasoning

arXiv:2606. 07299v1 Announce Type: new Abstract: Deep Research (DR) has emerged as a new agentic paradigm to tackle complex, open-ended research tasks, demanding systems that can iteratively frame problems, acquire evidence, verify sources, and synthesize long-form reports.

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arXiv Machine Learning

Jun 29

COOPA: A Modular LLM Agent Architecture for Operations Research Problems

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arXiv Machine Learning

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The Hitchhiker's Guide to Agentic AI: From Foundations to Systems

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arXiv AI

Jun 3

Co-evolving Agent Architectures and Interpretable Reasoning for Automated Optimization

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arXiv AI

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PDDLCoder: Agentic PDDL Generation for LLM-Assisted Symbolic Planning

arXiv:2608. 16637v1 Announce Type: new Abstract: LLMs remain unreliable for long-horizon planning, often generating logically inconsistent or non-applicable plans.

By Veit Laule, Jiangtao Shuai, Manfred Hauswirth, Sonja Schimmler

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