Large Language Model-Guided Optimization

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QDEvo: A Multi-Objective Quality-Diversity Framework for Automated Heuristic Design
Jul 6, 2026Nam Do Khanh, Nhat Nguyen Tran Minh, Dat Pham Vu Tuan +2Automated Algorithm Discovery Automated Heuristic Design
Hanoi University of Science and Technology Hanoi, Vietnam · George Mason University Fairfax, Virginia, USA
Optimizing Large Language Models for Causality Assessment in Pharmacovigilance: Developing a Performance Metric as Objective for Bayesian Hyperparameter Optimization
Jul 4, 2026Nicole Sonne Heckmann, Arnault-Quentin Vermillet, Søren Norlin Mølgaard +4Bayesian Optimization Large Language Model-Guided Optimization
Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark. · Safety Operations, Novo Nordisk, Søborg, Denmark. · Clinical Development Centre Denmark, Novo Nordisk, Søborg, Denmark. +1
SABLE: An NDA-Safe Closed-Loop LLM Framework for Analog Circuit Optimization in Industrial EDA Flows
Jul 4, 2026Xunqi Li, Chris H. KimPrivacy-Preserving Language Models Large Language Model-Guided Optimization
University of Minnesota, Twin Cities, US
LLM-Guided Transportation Hub Capacity Planning with Textual Business Inputs
Jul 4, 2026Xiaoyue Liu, Zheng DongLarge Language Model-Guided Optimization Natural Language to Optimization Modeling
H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, USA.
SwarmResearch: Orchestrating Coding Agents for Open-Ended Discovery
Jul 2, 2026Yuvraj Virk, Zack Edds, Chunqiu Steven Xia +1Automated Algorithm Discovery Large Language Model-Guided Optimization
University of Illinois Urbana-Champaign
Understanding Agent-Based Patching of Compiler Missed Optimizations
Jul 2, 2026Batu Guan, Zirui Wang, Shaohua LiAI Coding Agents Large Language Model-Guided Optimization
The Chinese University of Hong Kong · Hong Kong SAR
Evolutionary Feature Engineering for Structured Data
Jul 2, 2026Ege Onur Taga, Yilin Zhuang, M. Emrullah Ildiz +4Large Language Model-Guided Optimization Time Series Forecasting
University of Michigan · Google Research
Active-GRPO: Adaptive Imitation and Self-Improving Reasoning for Molecular Optimization
Jul 1, 2026Xuefeng Liu, Mingxuan Cao, Qinan Huang +3Molecular Optimization Large Language Model-Guided Optimization
School of Medicine, Stanford University · 2Data Science Institute, University of Chicago · 3Pritzker School of Molecular Engineering, University of Chicago +2
Adaptive Cluster-First Route-Second Decomposition for Industrial-Scale Vehicle Routing
Jun 30, 2026Oguzhan Karaahmetoglu, Hyong KimLarge Language Model-Guided Optimization Combinatorial Optimization
Carnegie Mellon University · Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213 USA
RAISE: LLM-based Automated Heuristic Design with Robust Adversary Instance Search
Jun 30, 2026Fei Liu, Alessio Figalli, Patrick Owen +1Distribution Shift Robustness Automated Algorithm Discovery
University of Zurich · 2ETH Zurich
AI-Assisted Discovery of Convex Relaxations via Dual Agents
Jun 30, 2026Sungyoon Kim, Mert PilanciPrimal-Dual Optimization AI Agents for Scientific Discovery
Department of Electrical Engineering, Stanford University, CA, USA.
Semantics-Aware Bilevel Co-Evolution: Towards Automated Multicomponent Algorithm Design
Jun 29, 2026Zhiyao Zhang, Shenghao Wu, Xingyu Wu +1Automated Algorithm Discovery Evolutionary Optimization
Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University, Hong Kong SAR 999077, China · College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China
AI Training Manager: Bounded Closed-Loop Control of Adaptive Training Recipes
Jun 29, 2026Anjali Rao, Nikhil Kamalkumar AdvaniLanguage Model-Based Control Large Language Model-Guided Optimization
Independent Researcher Mountain View, California
Optimizing Expert-Designed Crystal Graph Networks for Band-Gap Prediction with an Autonomous LLM Research Loop
Jun 29, 2026Chenmu Zhang, Boris I. YakobsonGraph Neural Networks Large Language Model-Guided Optimization
Department of Materials Science and NanoEngineering Rice University Houston, TX 77005, USA
SemJoin: Semantic Join Optimization
Jun 28, 2026Christopher Gou, Aditya Banerjee, Jiaxuan Wang +1Large Language Model-Guided Optimization Cost-Aware Inference
Purdue University
Interpretable Inverse Design of Metal-Organic Frameworks with Large Language Model Agents
Jun 28, 2026Kyungmin Nam, Seunghee Han, Jihan KimLarge Language Model-Guided Optimization Large Language Model-Guided Scientific Discovery
Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.
Solver-Verified Formulation Generation and Selection for Multi-Warehouse Inventory Allocation Using Large Language Models
Jun 28, 2026Jintao Xu, Yingzheng Ma, Jiong Dong +4Inventory Control Mixed-Integer Linear Programming
Supply Chain Tech Team Y, JD.com
Evolution Fine-Tuning: Learning to Discover Across 371 Optimization Tasks
Jun 27, 2026Young-Jun Lee, Seungone Kim, Minki Kang +5Supervised Fine-Tuning Evolutionary Optimization
University of Minnesota · Carnegie Mellon University · KAIST +3
EGG: An Expert-Guided Agent Framework for Kernel Generation
Jun 25, 2026Yaochen Han, Ke Fan, Hongxu Jiang +5GPU Kernel Optimization Large Language Model-Guided Optimization
Beihang University, Beijing, China · Shanghai Jiao Tong University, Shanghai, China · Tsinghua University, Beijing, China +1
Optimizing CUDA like a Human: Micro-Profiling Tools as Expert Surrogates for LLM-Based GPU Kernel Optimization
Jun 24, 2026Jiading Gai, Shuai Zhang, Kaj Bostrom +6GPU Kernel Optimization High-Performance Computing
Amazon · Siemens · University of Minnesota
MiniOpt: Reasoning to Model and Solve General Optimization Problems with Limited Resources
Jun 24, 2026Ke Zhao, Zixiang Di, Hong Qian +9Large Language Model-Guided Optimization RL for Language Model Reasoning
East China Normal University, Shanghai 200062, China · AntGroup, Hangzhou 310000, China · Southern University of Science and Technology, Shenzhen 518055, China +1
ASAP: Agent-System Co-Design for Wall-Clock-Centered Auto HPO Research for ML Experiments
Jun 23, 2026Taicheng Guo, Haomin Zhuang, Kehan Guo +4LLM Inference Efficiency Large Language Model-Guided Optimization
University of Notre Dame United States
GRIMIP: A General Framework for Instance-Specific Configuration of MIP Solvers Using LLMs
Jun 22, 2026Yidong Luo, Xuemin Chen, Chenguang Wang +3Surrogate-Assisted Optimization Mixed-Integer Linear Programming
School of Data Science, The Chinese University of Hong Kong, Shenzhen · School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen · Noah’s Ark Lab, Huawei
YUKTI: From Natural-Language Situations to Robust, Verifiable Decisions An Uncertainty-Typed Proposition IR, Assumption-Robust Pareto Frontiers, and a Regret Certificate
Jun 22, 2026Suyash MishraLarge Language Model-Guided Optimization Robust Optimization
AI Researcher
InstructFX2FX: A Multi-Turn Text-to-Effect System for Sequential Audio Effect Refinement
Jun 20, 2026Song-Ze Yu, Milan Liessens Dujardin, Yuxuan Cai +4Text-to-Audio Generation Large Language Model-Guided Optimization
Center for New Music and Audio Technologies (CNMAT) University of California, Berkeley
AgentDSE: Reasoning-Augmented Architectural Design Space Exploration
Jun 20, 2026Chenyu Wang, Jiahe Caroline Shi, David Kong +4Large Language Model-Guided Optimization Electronic Design Automation
Harvard University · Massachusetts Institute of Technology · Columbia University
When Is an LLM Worth It for Hyperparameter Optimization? A Budget-Matched Study on Tabular Data Finds the Warm-Start Is a Default Configuration, Not the Model
Jun 19, 2026Carson Rodrigues, Oysturn Vas, Isaiah Abner DCosta +1Large Language Model-Guided Optimization Hyperparameter Optimization
Celabe · University of Waterloo · University of Queensland (EAIT)
AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning
Jun 18, 2026Zepeng Li, Jie Ren, Zhanyong Tang +2Large Language Model-Guided Optimization
Shaanxi Normal University · China · Northwest University +2
FAPO: Fully Automated Prompt Optimization of Multi-Step LLM Pipelines
Jun 17, 2026Paul Kassianik, Baturay Saglam, Huaibo Zhao +4Large Language Model-Guided Optimization LLM Agent Workflow Optimization
Foundation AI–Cisco Systems Inc. · Yale University
SAGE: Stochastic Prompt Optimization via Agent-Guided Exploration
Jun 17, 2026Ziyi Zhu, Luka Smyth, Saki Shinoda +1Large Language Model-Guided Optimization Automatic Prompt Optimization
1Slingshot AI · Department of Engineering, University of Cambridge

Jul 6, 2026, cs.NEJ/K move · Enter open · S save

QDEvo: A Multi-Objective Quality-Diversity Framework for Automated Heuristic Design

Nam Do Khanh, Nhat Nguyen Tran Minh, Dat Pham Vu Tuan, Long Doan+1

Hanoi University of Science and Technology Hanoi, Vietnam · George Mason University Fairfax, Virginia, USA

Automated Algorithm Discovery Automated Heuristic Design Metaheuristic Optimization Large Language Model-Guided Optimization Combinatorial Optimization Quality-Diversity Optimization+1

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The integration of Large Language Models (LLMs) with evolutionary computation has emerged as a powerful paradigm for automated heuristic design in combinatorial optimization. However, existing approaches suffer from mode collapse, converging to homogeneous populations that lack semantic diversity and fail to explore the full algorithmic space. We propose Quality-Diversity Evolution (QDEvo), a multi-objective framework that integrates Quality-Diversity optimization with LLM-driven heuristic search, maintaining an unbounded archive of semantically diverse algorithms using pre-trained code embeddings and incorporating hierarchical self-reflection to guide the evolutionary process. Extensive experiments across standard benchmarks and real-world industrial applications demonstrate that QDEvo significantly outperforms state-of-the-art methods in both Hypervolume and Inverted Generational Distance metrics. Our framework enables the discovery of heuristics that are simultaneously high-performing, computationally efficient, and semantically diverse, providing practitioners with a rich portfolio of solutions for complex optimization problems.

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