Large Language Model-Guided Optimization

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67 papers in the last four weeks, up 219% on the four weeks before. 0.7% of all new papers.

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LLMZero: Discovering Adaptive Training Strategies for RL Post-Training via LLM Agents
Jun 16, 2026Haoyang Fang, Wei Zhu, Boran Han +11Reinforcement Learning Large Language Model-Guided Optimization
†LLMZero Project Core Team. · ∗Work done at Amazon.
OmniPlan: An Adaptive Framework for Timely and Near-Optimal Network Planning Optimization
Jun 16, 2026Longlong Zhu, Jiashuo Yu, Zedi Chen +12Algorithm Selection Large Language Model-Guided Optimization
Zhejiang University Hangzhou, Zhejiang, China · College of Computer and Data Science Fuzhou University Fuzhou, Fujian, China · Yangzhou University Yangzhou, Jiangsu, China +1
AUTOGATE: Automated Clock Gating via Toggling-Aware LLM-based RTL Rewriting
Jun 16, 2026Yiting Wang, Chenhui Deng, Chia-Tung Ho +6Large Language Model-Guided Optimization Electronic Design Automation
University of Maryland, College Park · NVIDIA
daVinci-kernel: Co-Evolving Skill Selection, Summarization, and Utilization via RL for GPU Kernel Optimization
Jun 15, 2026Dayuan Fu, Mohan Jiang, Tongyu Wang +5RL for Code Generation GPU Kernel Optimization
1SII · 2SJTU · 3GAIR
REFLEX: Reflective Evolution from LLM Experience
Jun 15, 2026Pan WangEvolutionary Optimization Large Language Model-Guided Optimization
University of Science and Technology of China, China.
Embedded Arena: Iterative Optimization via Hardware Feedback
Jun 15, 2026Zhihan Zhang, Alexander Le Metzger, Jiuyang Lyu +10Large Language Model-Guided Optimization Tiny ML
University of Washington · University of California San Diego · Northeastern University
Heteroskedastic Signals in Budgeted LLM Verification: Structural Heterogeneity Limits Optimization Gains
Jun 14, 2026Jinlong YangLarge Language Model-Guided Optimization LLM Uncertainty Estimation
Northwestern Polytechnical University
Pepti-Agent: An AI Agent for Peptide Design and Optimization
Jun 13, 2026Houxu Chen, Achuth Chandrasekhar, Amir Barati FarimaniAI Agents for Scientific Discovery Large Language Model-Guided Optimization
Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA · Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA · Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA +2
Large Language Model-Driven Cooperative Operator Ensemble Evolution for Permutation Flow Shop Scheduling
Jun 13, 2026Rui Xu, Yufan Liao, Haoze Lv +3Evolutionary Optimization Metaheuristic Optimization
School of Business, Hohai University, Nanjing 211100, China · Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China · School of Engineering and Computer Science, Victoria University of Wellington, Wellington 6140, New Zealand
StarOR: Synergizing Tree Search and Test-Time Reinforcement Learning for Optimization Modeling
Jun 13, 2026Jiajun Li, Yu Ding, Shisi Guan +2Reinforcement Learning Large Language Model-Guided Optimization
School of Computer Science and Engineering, Southeast University · Northwest A&F University
PANDA: An LLM-Enhanced Performance-Driven Analog Design Framework Bridging Design Intent and Layout Generation
Jun 13, 2026Haoyi Zhang, Weijian Fan, Xiaohan Gao +3Large Language Model-Guided Optimization Electronic Design Automation
School of Integrated Circuits, Peking University, Beijing, China · Beijing Advanced Innovation Center for Integrated Circuits, Beijing, China · Institute of Electronic Design Automation, Peking University, Wuxi, China
Remember, Don't Re-read: Stateful ReAct Agents for Token-Efficient Autonomous Experimentation
Jun 12, 2026Faramarz JabbarvaziriLarge Language Model-Guided Optimization LLM Agent Workflow Optimization
CARE: Context-Aware Ranking Evolution with Executable Scoring Programs for Budgeted Reaction Optimization
Jun 12, 2026Guanyu Liu, Weiyi Kong, Chao Tang +5Large Language Model-Guided Optimization Program Synthesis
University of Macau · University of Toronto · UCLA +3
MeEvo: Metacognitive Evolution Combined with Natural Evolution for Automatic Heuristic Design
Jun 12, 2026Zishang Qiu, Xinan Chen, Rong Qu +1Automated Heuristic Design Evolutionary Optimization
School of Computer Science, University of Nottingham Ningbo China, Ningbo, China · School of Computer Science, University of Nottingham, Nottingham, UK
Graph-based Target Back-Propagation for Context Adaptation in Multi-LLM Agentic Systems
Jun 12, 2026Tan Zhu, Tong Yao, Kananart Kuwaranancharoen +4Multi-Agent LLM Systems Large Language Model-Guided Optimization
Retail Intelligence, Walmart Global Tech, Sunnyvale, CA, USA
Multi-Objective Coevolution of Prompts and Templates for Circuit Approximation
Jun 11, 2026Martin Tomasovic, Lukas SekaninaMulti-Objective Evolutionary Optimization Large Language Model-Guided Optimization
Brno University of Technology, Faculty of Information Technology Brno, Czech Republic
JailbreakOPT: Tool-Assisted Iterative Jailbreak Prompt Optimization
Jun 9, 2026Ge Shi, Jun Yin, Donglin Xie +3Adversarial Prompt Generation Large Language Model-Guided Optimization
University of California, Davis · The Renmin University of China · Independent Researcher +3
FlowBank: Query-Adaptive Agentic Workflows Optimization through Precompute-and-Reuse
Jun 9, 2026Lingzhi Yuan, Chenghao Deng, Fangxu Yu +3Multi-Agent LLM Systems Multi-Agent System Optimization
University of Maryland, College Park · Amazon
Towards Autonomous Accelerator Design: FPGA Accelerator Generation with SECDA
Jun 9, 2026Vinamra Sharma, Xingjian Fu, Jude Haris +1Large Language Model-Guided Optimization Electronic Design Automation
School of Computing Science, University of Glasgow, Scotland, UK
Structure from Reasoning, Numbers from Search: On-Premise Open LLMs as Structural Priors for Coupled MIMO Controller Tuning
Jun 9, 2026Jiaxuan Chen, Haonan Li, Yang ShuLanguage Model-Based Control Large Language Model-Guided Optimization
Jinling Institute of Technology, Nanjing, China · College of Water Resources and Civil Engineering, China Agricultural University, Beijing, China · Zhejiang University, Hangzhou, China
Beyond Static Evaluation: Co-Evolutionary Mechanisms for LLM-Driven Strategy Evolution in Adversarial Games
Jun 9, 2026Haoran Li, Zengle Ge, Ziyang Zhang +10Game-Playing Agents Evolutionary Optimization
University of Chinese Academy of Sciences · Famou Agent Team, Baidu AI Cloud · The University of Sydney, Australia +3
LLM-Guided Neural Architecture Search for Robust Co-Design of Physical Neural Networks
Jun 9, 2026Tyler King, Timothee LeleuEnergy-Efficient ML Large Language Model-Guided Optimization
NTT Research · Princeton University · Stanford University
Sim2Schedule: A Simulator-Guided LLM Framework for Autonomous Open-Pit Mine Scheduling
Jun 9, 2026Mustavi Ibne Masum, Thiago Eustaquio Alves de Oliveira, Mahzabeen EmuLarge Language Model-Guided Optimization Model-Based Planning
Department of Computer Science, Lakehead University, Canada · Quantum Communications and Computing Research Center and Department of Electrical and Computer Engineering, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
How Far Can Prompting Go for Minimal-Edit Ukrainian Grammatical Error Correction?
Jun 8, 2026Kateryna Karpo, Artem ChernodubLLM Evaluation LLM Prompting
Ukrainian Catholic University · YouScan · Zendesk
Order Matters: Unveiling the Hidden Impact of Macro Placement Sequences via Proxy-Guided LLM Evolution
Jun 8, 2026Shibing Mo, Jing Liu, Jianchu Xu +1Automated Algorithm Discovery Large Language Model-Guided Optimization
the School of Artifcial Intelligence, Xidian University · the Guangzhou Institute of Technology, Xidian University.
Agentic Search for Counterfactual Recourse under Fixed LLM Budgets
Jun 7, 2026Yasuo TabeiCounterfactual Explanations Large Language Model-Guided Optimization
RIKEN Center for Advanced Intelligence Project Tokyo, Japan
LLM-Guided Evolution for Medical Decision Pipelines
Jun 5, 2026Ivan Sviridov, Artem Oskin, Ivan Panin +4Clinical Triage Large Language Model-Guided Optimization
1Sber AI Lab · 2AIRI
AgentCompile: An LLM-Guided Compiler for Direct CUDA Inference
Jun 4, 2026Xuanzhe Li, Ziyan Weng, Zhiyu Zhu +1Efficient Transformer Inference GPU Acceleration
City University of Hong Kong (Dongguan) · City University of Hong Kong
LLM-Guided ANN Index Optimization for Human-Object Interaction Retrieval
Jun 3, 2026Shahrzad Esmat, Chaunte W. Lacewell, Sameh Gobriel +2Large Language Model-Guided Optimization Hyperparameter Optimization
Iowa State University · Intel Corporation
Step-by-Step Optimization-like Reasoning in LLMs over Expanding Search Spaces
Jun 3, 2026Nicolás Astorga, Nabeel Seedat, Mihaela van der SchaarInference-Time Search Large Language Model-Guided Optimization
University of Cambridge

Jun 16, 2026, cs.LGJ/K move · Enter open · S save

LLMZero: Discovering Adaptive Training Strategies for RL Post-Training via LLM Agents

Haoyang Fang, Wei Zhu, Boran Han, Alex Zhang+10

†LLMZero Project Core Team. · ∗Work done at Amazon.

Reinforcement Learning Large Language Model-Guided Optimization RL Post-Training

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RL post-training strategies are dataset-dependent and reveal a recurring empirical pattern: capacity parameters accumulate monotonically across stages, while regularization parameters predominantly oscillate in response to shifting training dynamics. This distinction highlights a potential flaw in fixed training schedules: by forcing all parameters along rigid paths, they fail to capture the dynamic exploration-exploitation tradeoffs that regularization must track. We uncover this through LLMZero, an agentic system that optimizes training trajectories via tree search by diagnosing pathologies at each checkpoint and proposing coordinated multi-parameter transitions. Across four diverse GRPO tasks, LLMZero discovers strategies that improve over the base model by 9% to 140% and over grid search by 6% to 15% (relative), consistently outperforming random search and a skill-based agent under a matched compute budget. The capacity--regularization asymmetry is consistent across all four tasks, offering a candidate design heuristic for multi-stage training.

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