Black-Box Optimization

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6 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

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How Much Prompt Is Enough? A Blackbox Minimization of Few-Shots in LLMs
Sep 28, 2026Ali Alfageeh, Rahul Gopinath, Amin AlipourPrior Prompt Optimization Techniques Prompt Engineering
University of Houston · The University of Sydney
Hyper Algorithm Design Agent: Evolving Learnable Optimizer from Zero
Sep 28, 2026Zipei Yu, Yue-Jiao Gong, Zeyuan Ma +2Agentic Optimization Black-Box Optimization
South China University of Technology · South China Normal University · Singapore Management Univeristy
BOReFT: Manifold Steering of Language Models for Black-box Optimization
Sep 27, 2026Dhruv Agarwal, Rico Angell, Kavitha Srinivas +4Bayesian Optimization Black-Box Optimization
University of Massachusetts Amherst · New York University · IBM Research +1
BOBA: Dynamic Bayesian Optimization through Bayesian Active Inference
Sep 22, 2026Merlin Angel Kelly, Rishan Patel, Alexander Thomas +4Bayesian Optimization Black-Box Optimization
Department of Computer Science UCL Aspire Create University College London · Department of Electronic and Electrical Engineering University College London · UCL Aspire Create University College London
A practical DIRECT-type algorithm for medium-scale black-box global optimization
Sep 9, 2026Linas Stripinis, Remigijus PaulavičiusBlack-Box Optimization Black Box
Vilnius University Institute of Data Science and Digital Technologies, Akademijos 4, Vilnius, Lithuania, LT-08663
Constraint-Aware Discrete Black-Box Optimization Using Tensor Decomposition
Sep 8, 2026Keisuke Onoue, Ryosuke KojimaBlack-Box Optimization Tensor Decomposition
Nara Institute of Science and Technology, Nara, Japan · Graduate School of Medicine, Kyoto University, Kyoto, Japan · RIKEN Center for Biosystems Dynamics Research, Japan
Rethinking Learnability in Offline Data-driven Optimization
Sep 1, 2026Chao Qian, Chen-Guang Wang, Rong-Xi Tan +1Black-Box Optimization Learnability
State Key Laboratory of Novel Software Technology, Nanjing University, Nanjing 210023, China · School of Artificial Intelligence, Nanjing University, Nanjing 210023, China
Large-scale Testing Global Optimization Methods with Black-box Adversarial Attacks
Aug 13, 2026Wojciech Zarzecki, Jarosław ArabasBlack-Box Optimization Black-Box Adversarial Attacks
Warsaw University of Technology, Institute of Computer Science
Exploiting Separability in Multi-Scale Grey-Box Bayesian Optimization
Aug 4, 2026Joshua E. Hammond, Tyler A. Soderstrom, Brian A. Korgel +1Black-Box Optimization Bayesian Optimization
McKetta Department of Chemical Engineering, The University of Texas at Austin, 200 E. Dean Keaton St. Stop C0400, Austin, Texas 78712, USA · ExxonMobil Technology and Engineering, 22777 Springwoods Village Pkwy, Spring, Texas 77389, USA · Energy Institute, The University of Texas at Austin, 2304 Whitis Ave. Stop C2400, Austin, Texas 78712, USA +1
SCOPE: Synthetic Conditional Objectives for Policy Evolution in Black-Box Combinatorial Optimization
Jul 30, 2026Nguyen Viet Tuan Kiet, Nguyen Huu Duc, Le Cong Bang +2Black-Box Optimization Objective Functions
1Hanoi University of Science and Techonology, Hanoi, Vietnam · University of Sydney, Sydney, Australia
NeurGO: Learning to Generate Elite Candidates for Meta-Black-Box Expensive Optimization
Jul 26, 2026Jintao He, Huixiang Zhen, Wenyin GongBlack-Box Optimization Bayesian Optimization
China University of Geosciences, Wuhan, China
Black-Box Optimization for Identifying and Inverting Audio Dynamic Range Control Effects
Jul 22, 2026Haoran Sun, Dominique Fourer, Hichem MaarefBlack-Box Optimization Audio Understanding
IBISC (EA 4526), Univ. Évry Paris-Saclay
Unsupervised Multi-kernel Learning for Automated Algorithm Selection
Jul 21, 2026Yihang Lu, Tome Eftimov, Carola DoerrAlgorithm Selection Black-Box Optimization
Sorbonne Université, CNRS, INRAE, IRD, iEES, Paris, France · LIP6, Sorbonne Université, CNRS, Paris, France · Computer Systems Department, Jožef Stefan Institute, Ljubljana, Slovenia
Confidence-based Ranking with Adaptive Sampling for Noisy Black-Box Optimisation
Jul 16, 2026Enrico Halim, Hemant Kumar Singh, Tapabrata RayBlack-Box Optimization Genetic Algorithms
The University of New South Wales, Canberra, Australia
Maximally Robust Satisficing Bayesian Optimization
Jul 15, 2026Samuli Kinnunen, Petrus Mikkola, Antti Niskanen +1Bayesian Optimization Robust Optimization
Department of Computer Science, University of Helsinki, Finland · ASM International N.V.
Generative Refinement for Low-Budget Black-Box Optimization
Jul 1, 2026Edouard R. Dufour, Oliver Heinimann, Pascal FuaBlack-Box Optimization Prompt Optimization
CVLab EPFL Lausanne, CH
Bridging Spherical Black-Box Optimizers
Jun 24, 2026Johannes Ackermann, Stefano PeluchettiBlack-Box Optimization Optimizer Design
The University of Tokyo · Sakana AI
\chisao{}: A GPU-Native Parallel Optimizer for Multimodal Black-Box Functions via Convergence-Anticonvergence Oscillation
Jun 24, 2026Ira WolfsonBlack-Box Optimization Cpu-Gpu Hybrid Designs
Department of Electronics and Electrical Engineering Braude College of Engineering, Karmiel, Israel
Stage-dependent integer-binary encoding in factorization-machine black-box optimization
Jun 22, 2026Ryo Ogawa, Mayumi Nakano, Yuya Seki +1Quadratic Unconstrained Binary Optimization Black-Box Optimization
Graduate School of Science and Technology, Keio University, Kanagawa 223-8522, Japan · Keio University Sustainable Quantum Artificial Intelligence Center (KSQAIC), Keio University, Tokyo 108-8345, Japan · Department of Applied Physics and Physico-Informatics, Keio University, Kanagawa 223-8522, Japan +2
Zero-Inflated Gaussian Distributions Enable Parameter-Space Sparsity in Estimation-of-Distribution Algorithms
Jun 11, 2026Andreas Faust, Sven Nitzsche, Juergen BeckerEvolutionary Optimization Sparsity
University of Freiburg, Freiburg, Germany · FZI Research Center for Information Technology, Karlsruhe, Germany · Karlsruhe Institute of Technology, Karlsruhe, Germany
Mixed-Categorical Black-Box Optimization via Information-Geometric Bilevel Decomposition
Jun 11, 2026Marc Ong, Shinichi Shirakawa, Youhei AkimotoBilevel Optimization Black-Box Optimization
University of Tsukuba, Tsukuba, Japan · Yokohama National University, Yokohama, Japan · RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
Quantitative Performance Analysis of Stopping Criteria for CMA-ES
Jun 8, 2026Ryoji TanabeBlack-Box Optimization Covariance
Yokohama National University, Yokohama, Japan
Gray-Box Optimization and the Vertex Coloring Problem
Jun 6, 2026Johanna Gasse, Antonia Heinen, Hendrik Higl +1Black-Box Optimization Combinatorial Optimization
Hasso Plattner Institute University of Potsdam Potsdam, Germany
Meta-Black-Box Optimization with Ensemble Surrogate Modeling for Robustness-Accuracy Trade-off within SAEA
May 30, 2026Xiao Jin, Yongxiong Wang, Haobo Liu +2Black-Box Optimization Surrogate Models
School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, 200093, Shanghai, China · Xinxiang University, 453003, Xinxiang, China · College of System Engineering, National University of Defense Technology, 410073, Changsha, China
Performance and Explainability Requirements of Evolutionary Algorithms in Real-World Physics-Informed Optimization
May 27, 2026Helena Stegherr, Michael Heider, Nils Meyer +7Evolutionary Optimization Genetic Algorithms
Universität Augsburg, Germany · Universität Augsburg, Augsburg, Germany
On the Structural (Dis)Agreement of Landscape Representations in Black-Box Optimization
May 27, 2026Sara Gjorgjieva, Eva Tuba, Barbara Koroušić Seljak +2Black-Box Optimization Optimization Landscape
Jožef Stefan Institute, Ljubljana, Slovenia · Sorbonne Université, CNRS, LIP6, Paris, France
An Open-Source Training Dataset for Foundation Models for Black-box Optimization
May 22, 2026Aaron Klein, Herilalaina Rakotoarison, Luca Thale-Bombien +1Black-Box Optimization Real-World Dataset
University of Helsinki · ELLIS Institute Tübingen, Prior Labs
Regret-Based $(ε,δ)$ -optimal Stopping Criteria for Bayesian Optimization
May 21, 2026Haowei Wang, Jingyi Wang, Qiyu WeiBayesian Optimization Optimal Stopping
National University of Singapore, Singapore · Lawrence Livermore National Laboratory, CA, USA · The University of Manchester, UK
Beyond Numerical Features: CNN-Driven Algorithm Selection via Contour Plots for Continuous Black-Box Optimization
May 20, 2026Yiliang Yuan, Xiang Shi, Mustafa MisirBlack-Box Optimization Algorithm Selection
Mohamed bin Zayed University of Artificial Intelligence, Masdar City, United Arab Emirates · Duke Kunshan University, Suzhou, China
BoLT: A Benchmark to Democratize Black-box Optimization Research for Expensive LLM Tasks
May 16, 2026Ruth Wan Theng Chew, Zhiliang Chen, Apivich Hemachandra +1Large Language Model Benchmarks Black-Box Optimization
National University of Singapore
WASHH: An Anchor-Aware Whale-Guided Selection Hyper-Heuristic for Continuous Optimization and SVC Configuration
May 13, 2026Yifu Zhao, Xiaofan Zou, Junhao Wei +9Black-Box Optimization Metaheuristics
Faculty of Applied Sciences, Macao Polytechnic University, Macao, 999078, China · School of Mechanical and Electrical Engineering and Automation, Shanghai University, Shanghai, 200444, China · Pazhou Lab (Huangpu), Guangzhou, 510555, China +2
Black-Box Optimization of Mixed Binary-Continuous Variables: Challenges and Opportunities in Evolutionary Model Merging
May 12, 2026Md. Robiul Islam Niloy, Youhei AkimotoContinual Model Merging Optimization Modeling
BRAC University, Bangladesh
Support-Proximity Augmented Diffusion Estimation for Offline Black-Box Optimization
May 11, 2026Yonghan Yang, Ye Yuan, Zipeng Sun +5Black-Box Optimization
MBZUAI - Mohamed bin Zayed University of Artificial Intelligence · McGill University · Mila - Quebec AI Institute +1
Regret Analysis of Guided Diffusion for Black-Box Optimization over Structured Inputs
May 11, 2026Masaki Adachi, Anita Yang, Yakun Wang +1Black-Box Optimization Diffusion Models
Toyota Motor Corporation · Lattice Lab · University of Bristol
Meta-Black-Box Optimization Can Do Search Guidance for Expensive Constrained Multi-Objective Optimization
May 11, 2026Yukun Du, Haiyue Yu, Jiang Jiang +5Black-Box Optimization Multi-Objective Optimization
National University of Defense Technology, Changsha, Hunan, China.
ADKO: Agentic Decentralized Knowledge Optimization
May 8, 2026Lucas Nerone Rillo, Zhanhong Jiang, Nastaran Saadati +4Agentic Optimization Black-Box Optimization
Iowa State University · New York University
In-Context Black-Box Optimization with Unreliable Feedback
May 7, 2026Nicolas Samuel Blumer, Julien Martinelli, Samuel KaskiBlack-Box Optimization Bayesian Optimization
ELLIS Institute Finland · Aalto University · University of Manchester
On the Influence of the Feature Computation Budget on Per-Instance Algorithm Selection for Black-Box Optimization
May 6, 2026Koen van der Blom, Diederick VermettenAlgorithm Selection Black-Box Optimization
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands · Sorbonne Universit´e, CNRS, LIP6, Paris, France
Caliper-in-the-Loop: Black-Box Optimization for Hyperledger Fabric Performance Tuning
May 4, 2026Yash Madhwal, Arseny Bolotnikov, Mark Prikhno +5Black-Box Optimization Bayesian Optimization
Skolkovo Institute of Science and Technology, Moscow, Russia · HSE University, Moscow, Russia · Sberbank PJSC, Moscow, Russia +4
Black-box optimization of noisy functions with unknown smoothness
May 4, 2026Jean-Bastien Grill, Michal Valko, Rémi MunosBlack-Box Optimization Smoothness
SequeL team, INRIA Lille - Nord Europe, France · Google DeepMind, UK∗
Feasible-First Exploration for Constrained ML Deployment Optimization in Crash-Prone Hierarchical Search Spaces
Apr 27, 2026Christian LysenstøenEfficient Exploration Black-Box Optimization
Department of Electrical Engineering and Computer Sciences University of California, Berkeley
Rethinking Trust Region Bayesian Optimization in High Dimensions
Apr 24, 2026Wei-Ting Tang, Joel A. PaulsonMulti-Objective Bayesian Optimization Algorithms Trust Region
University of Wisconsin–Madison
BOOOM: Loss-Function-Agnostic Black-Box Optimization over Orthonormal Manifolds for Machine Learning and Statistical Inference
Apr 23, 2026Beomchang Kim, Subhrajyoty Roy, Priyam DasRiemannian Optimization Black-Box Optimization
Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA · Department of Statistics and Data Science, Washington University in St. Louis,[math.OC] St. Louis, MO, USA
Similarity-based Portfolio Construction for Black-box Optimization
Apr 20, 2026Catalin-Viorel Dinu, Diederick Vermetten, Carola DoerrBlack-Box Optimization Algorithm Selection
Sorbonne Université, CNRS, LIP6
RASP-Tuner: Retrieval-Augmented Soft Prompts for Context-Aware Black-Box Optimization in Non-Stationary Environments
Apr 20, 2026Enze PanBlack-Box Optimization Tuning
Department of Computer Science, The University of Hong Kong.
Stein Variational Black-Box Combinatorial Optimization
Apr 17, 2026Thomas Landais, Olivier Goudet, Adrien Goëffon +2Black-Box Optimization Stochastic Optimization
LERIA, Université d’Angers, 2 Boulevard Lavoisier, Angers 49045, France
Meta-Learning-Assisted Constraint Relaxation for Constrained Black-Box Optimization
Jan 31, 2026Sijie Ma, Zeyuan Ma, Yue-Jiao Gong +1Black-Box Optimization Meta-Learning
Hong Kong Polytechnic University · South China Normal University · South China University of Technology
Online Regime-aware Calibration for Black-box Social Simulators via Posterior-assisted Evolutionary Dynamic Optimization
Jan 27, 2026Peng Yang, Zhenhua Yang, Boquan Jiang +3Black-Box Optimization Robust Optimization
Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Southern University of Science and Technology, Shenzhen 518055, China · Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China · Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen 518055, China +2
How Sequential Algorithm Portfolios can benefit Black Box Optimization
Jan 23, 2026Catalin-Viorel Dinu, Diederick Vermetten, Carola DoerrBlack-Box Optimization Portfolio Construction
Sorbonne Universit´e, CNRS, LIP6 in Paris, France
Tuning without Peeking: Provable Generalization Bounds and Robust LLM Post-Training
Jul 2, 2025Ismail Labiad, Mathurin Videau, Matthieu Kowalski +4Privacy-Preserving Machine Learning Black-Box Optimization
Meta FAIR · Université Paris-Saclay · LISN, Inria, CNRS +2
Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies
Jun 30, 2025Tim Roith, Leon Bungert, Philipp WackerBlack-Box Optimization Black-Box Adversarial Attacks
TUM School of Computation, Information and Technology and Munich Center for Machine Learning (MCML), Boltzmannstr. 3, 85748 Garching bei München, Germany · Institute of Mathematics, Center for Artificial Intelligence and Data Science (CAIDAS), University of Würzburg, Emil-Fischer-Str. 40, 97074 Würzburg, Germany · School of Mathematics and Statistics, University of Canterbury
Probabilistic Approach to Black-Box Binary Optimization with Budget Constraints: Application to Sensor Placement
Jun 9, 2024Ahmed AttiaBayesian Experimental Design Black-Box Optimization
Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL, USA
MEGO: Learning Mixture-of-Experts for General-Purpose Binary Optimization
May 29, 2024Shengcai Liu, Zhiyuan Wang, Yew-Soon Ong +2Black-Box Optimization Combinatorial Optimization
Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China · College of Computing & Data Science, Nanyang Technological University, Singapore 639798 · School of Data Science, Lingnan University, Hong Kong, China
Code-to-Harness: Distilling Black-Box Optimizers from Self-Play
Date pendingYi Wu, Zheng Ren, Zhiyu Hu +8Agentic Optimization Agent Harness
Google Mountain View, USA

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How Much Prompt Is Enough? A Blackbox Minimization of Few-Shots in LLMs

Ali Alfageeh, Rahul Gopinath, Amin Alipour

University of Houston · The University of Sydney

Prior Prompt Optimization Techniques Prompt Engineering Fidelity Black-Box Optimization

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Prompts are the primary mechanism for directing the behavior of large language models (LLMs). Yet the internal structure and causal hierarchy of prompts remain poorly understood: which parts are causally necessary and which are redundant is an open question. This opacity can have severe consequences. Subtle prompt variations can silently shift model outputs in critical software systems, and engineers lack techniques to reason about prompt reliability. We present \framework, a blackbox prompt-minimization framework that reduces few-shot prompts to their necessary minimal subset. We use a case study to apply \framework to a few-shot learning system and demonstrate the insights that this framework can provide. Our experiments show that few-shot exemplars can be reduced by a mean of 65.3%~

\pm

~15.8% in character count while fully preserving propositional output fidelity. The models preferentially retain logical identifiers and constraint declarations while discarding natural language prose and cross-prompt relational annotations. Our analysis also shows that some models are universal encoders, able to produce highly legible yet minimized prompts, while others are universal decoders, able to interpret minimized prompts from most other models. By identifying which components are indispensable, \framework provides a principled basis for prompt compression and structural analysis of few-shot exemplars.

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