Papers Evolutionary Algorithms
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Zero-Shot Chain-of-Thought Reasoning Guided by Evolutionary Algorithms in Large Language Models
Large Language Models (LLMs) have demonstrated remarkable performance across diverse tasks and exhibited impressive reasoning abilities by applying zero-shot Chain-of-Thought (CoT) prompting. However, due to the evolving…
Evolutionary AlgorithmsSentenceBreaking Free: How to Hack Safety Guardrails in Black-Box Diffusion Models!
Deep neural networks can be exploited using natural adversarial samples, which do not impact human perception. Current approaches often rely on deep neural networks' white-box nature to generate these adversarial samples…
Evolutionary AlgorithmsImage GenerationMisclassification Rate - Natural Adversarial SamplesA Bandit Approach with Evolutionary Operators for Model Selection
This work formulates model selection as an infinite-armed bandit problem, namely, a problem in which a decision maker iteratively selects one of an infinite number of fixed choices (i.e., arms) when the properties of eac…
Evolutionary Algorithmsimage-classificationImage ClassificationModel SelectionDiffusion Model-Based Multiobjective Optimization for Gasoline Blending Scheduling
Gasoline blending scheduling uses resource allocation and operation sequencing to meet a refinery's production requirements. The presence of nonlinearity, integer constraints, and a large number of decision variables add…
Evolutionary AlgorithmsMultiobjective OptimizationSchedulingEvolution Guided Generative Flow Networks
Generative Flow Networks (GFlowNets) are a family of probabilistic generative models that learn to sample compositional objects proportional to their rewards. One big challenge of GFlowNets is training them effectively w…
Evolutionary AlgorithmsReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution
The omnipresence of NP-hard combinatorial optimization problems (COPs) compels domain experts to engage in trial-and-error heuristic design. The long-standing endeavor of design automation has gained new momentum with th…
Combinatorial OptimizationEvolutionary AlgorithmsReal Evaluations Tractability using Continuous Goal-Directed Actions in Smart City Applications
One of the most important challenges of Smart City Applications is to adapt the system to interact with non-expert users. Robot imitation frameworks aim to simplify and reduce times of robot programming by allowing users…
Evolutionary AlgorithmsEvolutionary Algorithms Simulating Molecular Evolution: A New Field Proposal
The genetic blueprint for the essential functions of life is encoded in DNA, which is translated into proteins -- the engines driving most of our metabolic processes. Recent advancements in genome sequencing have unveile…
DiversityEvolutionary AlgorithmsExplainable Benchmarking for Iterative Optimization Heuristics
Benchmarking heuristic algorithms is vital to understand under which conditions and on what kind of problems certain algorithms perform well. In most current research into heuristic optimization algorithms, only a very l…
BenchmarkingEvolutionary AlgorithmsSCAPE: Searching Conceptual Architecture Prompts using Evolution
Conceptual architecture involves a highly creative exploration of novel ideas, often taken from other disciplines as architects consider radical new forms, materials, textures and colors for buildings. While today's gene…
Evolutionary AlgorithmsA Tournament of Transformation Models: B-Spline-based vs. Mesh-based Multi-Objective Deformable Image Registration
The transformation model is an essential component of any deformable image registration approach. It provides a representation of physical deformations between images, thereby defining the range and realism of registrati…
Evolutionary AlgorithmsImage RegistrationEmoDM: A Diffusion Model for Evolutionary Multi-objective Optimization
Evolutionary algorithms have been successful in solving multi-objective optimization problems (MOPs). However, as a class of population-based search methodology, evolutionary algorithms require a large number of evaluati…
Computational EfficiencyEvolutionary AlgorithmsBridging Evolutionary Algorithms and Reinforcement Learning: A Comprehensive Survey on Hybrid Algorithms
Evolutionary Reinforcement Learning (ERL), which integrates Evolutionary Algorithms (EAs) and Reinforcement Learning (RL) for optimization, has demonstrated remarkable performance advancements. By fusing both approaches,…
Evolutionary Algorithmsreinforcement-learningReinforcement LearningReinforcement Learning (RL)A First Step Towards Runtime Analysis of Evolutionary Neural Architecture Search
Evolutionary neural architecture search (ENAS) employs evolutionary algorithms to find high-performing neural architectures automatically, and has achieved great success. However, compared to the empirical success, its r…
Binary ClassificationEvolutionary AlgorithmsNeural Architecture SearchPower System Resource Expansion Planning
Power System Resource Planning is the recurrent process of studying and determining what facilities and procedures should be provided to satisfy and promote appropriate future demands for electricity. The electric power …
Evolutionary AlgorithmsWhen Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challenges
Pre-trained large language models (LLMs) exhibit powerful capabilities for generating natural text. Evolutionary algorithms (EAs) can discover diverse solutions to complex real-world problems. Motivated by the common col…
Evolutionary AlgorithmsMulti-Task LearningPositionText GenerationQuality-Diversity Algorithms Can Provably Be Helpful for Optimization
Quality-Diversity (QD) algorithms are a new type of Evolutionary Algorithms (EAs), aiming to find a set of high-performing, yet diverse solutions. They have found many successful applications in reinforcement learning an…
DiversityEvolutionary AlgorithmsEvolutionary Computation in the Era of Large Language Model: Survey and Roadmap
Large language models (LLMs) have not only revolutionized natural language processing but also extended their prowess to various domains, marking a significant stride towards artificial general intelligence. The interpla…
Code GenerationEvolutionary AlgorithmsLanguage ModelingLanguage Modelling+3Evolutionary Multi-Objective Optimization of Large Language Model Prompts for Balancing Sentiments
The advent of large language models (LLMs) such as ChatGPT has attracted considerable attention in various domains due to their remarkable performance and versatility. As the use of these models continues to grow, the im…
Evolutionary AlgorithmsLanguage ModelingLanguage ModellingLarge Language Model+2Constrained Multi-objective Optimization with Deep Reinforcement Learning Assisted Operator Selection
Solving constrained multi-objective optimization problems with evolutionary algorithms has attracted considerable attention. Various constrained multi-objective optimization evolutionary algorithms (CMOEAs) have been dev…
Deep Reinforcement LearningEvolutionary Algorithmsreinforcement-learningReinforcement Learning