4 citations · 7 across the 11 of their papers we have counts for
5 papers · 1 filter
EvoGM: Learning to Merge LLMs via Evolutionary Generative Optimization
Tao Jiang, Xinmeng Yu, Chenhao Yi +5
Evolutionary model merging provides a powerful framework for the automated, training-free composition of LLMs through parameter-space search. However, existing methods predominantl…
Beyond Speedups: Hardware-Aware Evaluation of Evolutionary Algorithms on GPUs
Xinmeng Yu, Tao Jiang, Ran Cheng +2
Evolutionary algorithms (EAs) are increasingly executed on graphics processing units (GPUs) to exploit population-level parallelism. This shift changes the resource model under whi…
Evolutionary Generative Optimization: Towards Fully Data-Driven Evolutionary Optimization via Generative Learning
Tao Jiang, Kebin Sun, Zhenyu Liang +3
Recent advances in data-driven evolutionary algorithms (EAs) have demonstrated the potential of leveraging historical data to improve optimization accuracy and adaptability. Despit…
Tensorized Ant Colony Optimization for GPU Acceleration
Luming Yang, Tao Jiang, Ran Cheng
Ant Colony Optimization (ACO) is renowned for its effectiveness in solving Traveling Salesman Problems, yet it faces computational challenges in CPU-based environments, particularl…
GPU-accelerated Evolutionary Multiobjective Optimization Using Tensorized RVEA
Zhenyu Liang, Tao Jiang, Kebin Sun +1
Evolutionary multiobjective optimization has witnessed remarkable progress during the past decades. However, existing algorithms often encounter computational challenges in large-s…