Optimization and Metaheuristics
Applications of LLMs in optimization problems, including metaheuristics, evolutionary algorithms, and combinatorial optimization techniques
Optimization and Metaheuristics
Research on Large Language Models in Optimization and Metaheuristics
Supercharging Optimization Algorithms with AI
How LLMs are revolutionizing metaheuristic optimization techniques
Evolution of AI: Teaching LLMs to Design Algorithms
How GPT Models Can Automatically Generate Optimization Algorithms
AI Solving Complex Optimization Problems
How LLMs can automate industrial optimization at scale
Evolving Better Heuristics with AI
LLMs for Multi-objective Optimization Beyond Just Performance
AI-Designed Control Policies for Dynamic Systems
Using LLMs to generate interpretable code-based controllers
Foundation Models for MILP: Breaking Optimization Boundaries
Generalizing deep learning approaches across diverse optimization problems
AI-Powered Optimization for Business
Teaching LLMs to formulate and solve complex optimization problems
QUBE: Smarter AI for Hard Problems
Balancing Quality and Exploration in LLM-powered Heuristic Design
Bridging AI with Symbolic Reasoning
Enhancing LLMs with Formal Problem-Solving Capabilities
Supercharging LLMs with Monte Carlo Tree Search
A smarter approach to automatic heuristic design for optimization problems
Balancing Multiple Objectives in Deep Learning
Advanced gradient-based methods for handling competing priorities
Optimizing SAT Solvers with AI
Using LLMs to Uncover Hidden Problem Structures
Making RLHF More Efficient
Breakthrough in scaling reinforcement learning from human feedback
Advancing Black-Box Optimization
Refined Adaptive Zeroth-Order Methods for Scenarios Without Gradient Access
Self-Evaluation in Optimization
Applying LLM techniques to improve scheduling algorithms
AI-Powered Optimization for Physics Calculations
Using LLMs to solve complex Feynman integrals more efficiently
Bridging NLP and Optimization Modeling
A scalable framework for synthetic data that enhances LLM capabilities
LLMs as Optimization Strategists
Automating heuristic optimization with AI-powered planning
Optimizing Nonlinear Problems through Variable Aggregation
A novel approach to reduce computational complexity in engineering optimization
AI-Powered Vehicle Routing Solution
Automating complex logistics optimization with LLMs
Benchmarking LLMs for Evolutionary Optimization
Using large language models to enhance multi-objective optimization algorithms
Intelligent Mate Selection in Evolutionary Algorithms
Using LLMs to Enhance Optimization Strategies
LLMs as Scientific Problem Solvers
A novel bi-level optimization approach for scientific challenges
Automating Operations Research with AI
Leveraging LLMs to democratize complex optimization problems
Natural Language to Optimization Models
Bridging the gap between text and formal constraint models
Beyond Templates: Next-Gen Algorithm Design
Co-evolving structure and function for superior LLM-generated algorithms
AI-Powered Robot Task Scheduling
Leveraging Local LLMs for Secure Industrial Automation
Supercharging Tabular Data with AI-Driven Feature Engineering
Using LLMs as Evolutionary Optimizers to Enhance Predictive Models
Automating Optimization Systems with AI
Using LLMs to reduce cost and expertise barriers in decision support
Mathematical Reasoning with LLMs
Transforming AI-driven optimization and problem-solving
AI-Powered Photonic Design Breakthrough
Leveraging LLMs to Automatically Discover Optimization Algorithms
Harnessing LLM Knowledge for Smarter Feature Engineering
Integrating domain expertise to reduce computational costs in ML pipelines
Revolutionizing AI Architecture Design
How Arch-LLM leverages discrete representation learning for neural network generation
Enhancing Engineering Design with LLMs
Leveraging AI's in-context learning for smarter optimization
