Beidan Liu — accepted AI-conference papers

2026

$A_2$DEPT: Large Language Model–Driven Automated Algorithm Design via Evolutionary Program Trees

Bin Chen, Shouliang Zhu, Beidan Liu, Yong Zhao, Tianle Pu, Huichun Li +1

ICML 2026poster

Designing heuristics for combinatorial optimization problems (COPs) is a fundamental yet challenging task that traditionally requires extensive domain expertise. Recently, Large Language Model (LLM)-based Automated Heuristic Design (AHD) has shown promise in autonomously generating heuristic compone…

Cited by 0 Source ↗Scholar ↗

2026

Towards Autonomous UAV Visual Object Search in City Space: Benchmark and Agentic Methodology

Yatai Ji, Zhengqiu Zhu, Yong Zhao, Beidan Liu, Chen Gao, Yihao Zhao +3

AAAI 2026technical

Aerial Visual Object Search (AVOS) tasks in urban environments require Unmanned Aerial Vehicles (UAVs) to autonomously search for and identify target objects based on visual inputs without external guidance. Existing approaches struggle in complex urban environments due to redundant semantic process

Cited by 0 Source ↗PDF ↗Scholar ↗