ACM Transactions on Evolutionary Learning and Optimization (telo) Vol 6, Issue 2

Evolution Fine-Tuning: Using LLMs to Learn and Transfer Knowledge Across 371 Optimization Tasks

This paper introduces "Evolution Fine-Tuning" (EFT), a novel approach that uses Large Language Models (LLMs) integrated with evolutionary se

Understanding Reinforcement Learning for Model Training, and future directions with GRAPE

Bidirectional Evolutionary Search: A New Framework for Self-Improving Language Models

This paper introduces Bidirectional Evolutionary Search (BES), a novel search framework for self-improving language models that addresses li

Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents

Unified Framework for Black-Box Optimization Reveals Hybrid Methods Outperform Constituent Algorithms

This paper presents a unified theoretical framework connecting several black-box optimization (BBO) methods — Evolution Strategies (ES), Con

Unified Framework for Black-Box Optimization Reveals Hybrid Methods Outperform Constituent Algorithms

This paper presents a unified theoretical framework connecting several black-box optimization (BBO) methods — Evolution Strategies (ES), Con