LLM Agent Orchestration

LLM: Large Language Model

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26 papers in the last four weeks, up 53% on the four weeks before. 0.3% of all new papers.

Jul 13Week of Sep 28

Latest papers 294

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FlowCompile: An Optimizing Compiler for Structured LLM Workflows
May 13, 2026Junyan Li, Zhang-Wei Hong, Maohao Shen +2LLM Agent Orchestration Cost-Aware Inference
UMass Amherst · MIT-IBM Watson AI Lab · MIT
NIMO Controller: a self-driving laboratory orchestrator based on the Model Context Protocol
May 13, 2026Naruki Yoshikawa, Ryo TamuraLLM Agent Orchestration Human-in-the-Loop AI
National Institute for Materials Science, Tsukuba, Ibaraki, Japan · Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
A Multi-Agent Orchestration Framework for Venture Capital Due Diligence
May 13, 2026Grigorios Alexandrou, Katerina PramatariMulti-Agent LLM Systems LLM Agent Orchestration
Department of Management Science and Technology, Athens University ofMay Economics and Business (AUEB), Athens, Greece
An Agentic LLM-Based Framework for Population-Scale Mental Health Screening
May 13, 2026Giuliano Lorenzoni, Paulo Alencar, Donald CowanLLM Agent Orchestration Clinical NLP
University of Waterloo · Waterloo, Ontario, Canada
SHM-Agents: A Generalist-Specialist Integrated Agent System for Structural Health Monitoring
May 13, 2026Yuequan Bao, Xing Li, Huabin Sun +3LLM Agent Orchestration LLM Agents
Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, Harbin Institute of Technology, Harbin · Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education, Harbin Institute of Technology, Harbin · School of Civil Engineering, Harbin Institute of Technology, Harbin
Grid-Orch: An LLM-Powered Orchestrator for Distribution Grid Simulation and Analytics
May 12, 2026Boming Liu, Jin Dong, Jamie LianLLM Agent Orchestration LLM Tool Use
Electrification and Energy Infrastructures Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830 USA
Agent-Based Post-Hoc Correction of Agricultural Yield Forecasts
May 12, 2026Matthew Beddows, Aiden Durrant, Georgios LeontidisTime Series Forecasting LLM Agent Orchestration
School of Natural and Computing Sciences University of Aberdeen, UK · School of Computing Sciences University of East Anglia, UK · Department of Physics and Technology UiT The Arctic University of Norway
Harness Engineering as Categorical Architecture
May 12, 2026Bogdan BanuLLM Agent Orchestration LLM Agent Harnesses
CAX-Agent: A Lightweight Agent Harness for Reliable APDL Automation
May 12, 2026Chenying Lin, Yichen Hai, Yi He +3LLM Agent Orchestration LLM Agent Evaluation
Shanghai Ultradimension Technology Co., Ltd., Shanghai, China · College of Logistics Engineering, Shanghai Maritime University, Shanghai, 201306, China · School of Civil Aviation, Northwestern Polytechnical University, Xi’an 710072, China +3
Cochise: A Reference Harness for Autonomous Penetration Testing
May 12, 2026Andreas Happe, Jürgen CitoLLM Agent Orchestration LLM Agent Evaluation
TU Wien · Vienna, Austria
Shepherd: Enabling Programmable Meta-Agents via Reversible Agentic Execution Traces
May 11, 2026Simon Yu, Derek Chong, Ananjan Nandi +4LLM Agent Orchestration
1Northeastern University · 2Stanford University
Beyond Autonomy: A Dynamic Tiered AgentRunner Framework for Governable and Resilient Enterprise AI Execution
May 11, 2026Kai Pan, Rong HouLLM Agent Orchestration AI Agent Safety
A2A Lab
Deterministic vs. LLM-Controlled Orchestration for COBOL-to-Python Modernization
May 11, 2026Naing Oo Lwin, Rajesh KumarLLM Inference Efficiency Software Engineering
Bucknell University Lewisburg, PA, USA
FlashEvolve: Accelerating Agent Self-Evolution with Asynchronous Stage Orchestration
May 8, 2026Zhengding Hu, Mingge Lu, Zhen Wang +8LLM Agent Orchestration LLM Agent Workflow Optimization
University of California, San Diego · Georgia Institute of Technology
Self-Programmed Execution for Language-Model Agents
May 7, 2026Luke J. O'ConnorLLM Agent Orchestration LLM Agents
Harvard Medical School · Boston, MA 02115
NeuroAgent: LLM Agents for Multimodal Neuroimaging Analysis and Research
May 7, 2026Lujia Zhong, Yihao Xia, Jianwei Zhang +4Multi-Agent LLM Systems LLM Agent Orchestration
1Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California · 2Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California · 3Alfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California
Improving the Efficiency of Language Agent Teams with Adaptive Task Graphs
May 7, 2026Elizabeth Mieczkowski, Alexander Ku, Tiwalayo Eisape +5Multi-Agent Coordination LLM Agent Orchestration
Princeton University · University of Cambridge · MIT +1
More Is Not Always Better: Cross-Component Interference in LLM Agent Scaffolding
May 7, 2026Ming LiuLLM Agent Orchestration LLM Agent Evaluation
Amazon
Securing the Agent: Vendor-Neutral, Multitenant Enterprise Retrieval and Tool Use
May 6, 2026Francisco Javier Arceo, Varsha Prasad NarsingLLM Agent Orchestration AI Agent Security
Red Hat AI · Boston, USA
Design Conductor 2.0: An agent builds a TurboQuant inference accelerator in 80 hours
May 6, 2026The Verkor Team, Ravi Krishna, Suresh Krishna +1AI Accelerator Inference Multi-Agent LLM Systems
The Verkor Team
Uno-Orchestra: Parsimonious Agent Routing via Selective Delegation
May 6, 2026Zhiqing Cui, Haotong Xie, Jiahao Yuan +11Multi-Agent System Optimization Multi-Agent Orchestration
Project lead.
SADE: Symptom-Aware Diagnostic Escalation for LLM-Based Network Troubleshooting
May 6, 2026Kuan-Hao Tseng, Niruth Bogahawatta, Yasod Ginige +3LLM Agent Orchestration LLM Agents
University of Sydney, Sydney, Australia · University of New South Wales, Sydney, Australia
When Context Hurts: The Crossover Effect of Knowledge Transfer on Multi-Agent Design Exploration
May 5, 2026Saranyan VigrahamSoftware Engineering Agents LLM Agent Orchestration
Meta
Physics-Grounded Multi-Agent Architecture for Traceable, Risk-Aware Human-AI Decision Support in Manufacturing
May 5, 2026Danny Hoang, Ryan Matthiessen, Christopher Miller +5Manufacturing Multi-Agent LLM Systems
School of Mechanical, Aerospace, and Manufacturing Engineering, University of Connecticut, Storrs, CT, USA · Connecticut Center for Advanced Technology, East Hartford, CT, USA · Quinnipiac University, Hamden, CT, USA +1
From Intent to Execution: Composing Agentic Workflows with Agent Recommendation
May 5, 2026Kishan Athrey, Ramin Pishehvar, Brian Riordan +1LLM Agent Orchestration Multi-Agent Systems
Cisco Systems Inc.
ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration
May 4, 2026Ruofeng Yang, Yongcan Li, Shuai LiAI Agent Reliability Multi-Agent LLM Systems
Shanghai Jiao Tong University · Shanghai Innovation Institute
Reinforcement Learning for LLM-based Multi-Agent Systems through Orchestration Traces
May 4, 2026Chenchen ZhangMulti-Agent LLM Systems LLM Agent Orchestration
Independent Researcher
Beyond State Machines: Executing Network Procedures with Agentic Tool-Calling Sequences
May 4, 2026Purna Sai Garigipati, Onur Ayan, Kishor Chandra Joshi +1LLM Agent Orchestration Tool-Using Agents
Heisenberg Research Center, Huawei Technologies Duesseldorf GmbH, 80992 Munich, Germany · Eindhoven University of Technology, Eindhoven, The Netherlands
EngiAgent: Fully Connected Coordination of LLM Agents for Solving Open-ended Engineering Problems with Feasible Solutions
May 4, 2026Xiyuan Zhou, Ruixi Zou, Xinlei Wang +4Multi-Agent LLM Systems Software Engineering Agents
Nanyang Technological University · The Chinese University of Hong Kong, Shenzhen · INSAIT, Sofia University “St. Kliment Ohridski” +2
AAFLOW: Scalable Patterns for Agentic AI Workflows
May 4, 2026Arup Kumar Sarker, Mills Staylor, Aymen Alsaadi +3LLM Agent Orchestration Agentic Workflows
Department of Computer Science, Biocomplexity Institute and Initiative University of Virginia Charlottesville, VA, USA · Department of Computer Science, Rutgers University New Brunswick, NJ, USA · Biocomplexity Institute and Initiative University of Virginia Charlottesville, VA, USA +1

May 13, 2026, cs.CLJ/K move · Enter open · S save

FlowCompile: An Optimizing Compiler for Structured LLM Workflows

Junyan Li, Zhang-Wei Hong, Maohao Shen, Yang Zhang+1

UMass Amherst · MIT-IBM Watson AI Lab · MIT

LLM Agent Orchestration Cost-Aware Inference LLM Agent Workflow Optimization

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Structured LLM workflows, where specialized LLM sub-agents execute according to a predefined graph, have become a powerful abstraction for solving complex tasks. Optimizing such workflows, i.e., selecting configurations for each sub-agent to balance accuracy and latency, is challenging due to the combinatorial design space over model choices, reasoning budgets, and workflow structures. Existing cost-aware methods largely treat workflow optimization as a routing problem, selecting a configuration at inference time for each query according to the accuracy-latency objective used during training. We argue that structured LLM workflows can also be optimized from a compilation perspective: before deployment, the system can globally explore the workflow design space and construct a reusable set of workflow-level configurations spanning diverse accuracy-latency trade-offs. Drawing inspiration from machine learning compilers, we introduce FlowCompile, a structured LLM workflow compiler that performs compile-time design space exploration to identify a high-quality, reusable trade-off set. FlowCompile decomposes a workflow into sub-agents, profiles each sub-agent under diverse configurations, and composes these measurements through a structure-aware proxy to estimate workflow-level accuracy and latency. It then identifies diverse high-quality configurations in a single compile-time pass, without retraining or online adaptation. Experiments across diverse workflows and challenging benchmarks show that FlowCompile consistently outperforms heuristically optimized workflow configurations and routing-based baselines, delivering up to 6.4x speedup. The compiled configuration set further serves as a reusable optimization artifact, enabling flexible deployment under varying runtime preferences and supporting downstream selection or routing.

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Latest papers 294