9 citations · 19 across the 7 of their papers we have counts for
7 papers
Semantics-Guided Automatic Tensorization for Multiobjective Evolutionary Algorithms: A Multi-Agent Framework
Zhenyu Liang, Beichen Huang, Bowen Zheng +1
Multiobjective evolutionary algorithms (MOEAs) naturally expose population-level parallelism, but many mature implementations encode their computation in sequential program structu…
Persistent Recursive Worlds Enable Autonomous Software Evolution
Beichen Huang, Zhenyu Liang, Bowen Zheng +1
Complex software systems develop over timescales that exceed the lifespan of any individual coding agent. Most agentic software systems preserve continuity through persistent sessi…
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…
GPU-accelerated Evolutionary Many-objective Optimization Using Tensorized NSGA-III
Hao Li, Zhenyu Liang, Ran Cheng
NSGA-III is one of the most widely adopted algorithms for tackling many-objective optimization problems. However, its CPU-based design severely limits scalability and computational…
Bridging Evolutionary Multiobjective Optimization and GPU Acceleration via Tensorization
Zhenyu Liang, Hao Li, Naiwei Yu +2
Evolutionary multiobjective optimization (EMO) has made significant strides over the past two decades. However, as problem scales and complexities increase, traditional EMO algorit…
A Multi-objective Optimization Benchmark Test Suite for Real-time Semantic Segmentation
Yifan Zhao, Zhenyu Liang, Zhichao Lu +1
As one of the emerging challenges in Automated Machine Learning, the Hardware-aware Neural Architecture Search (HW-NAS) tasks can be treated as black-box multi-objective optimizati…
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…