Hengzhe Zhang

According to our database, Hengzhe Zhang authored at least 28 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation.

Fabrício Olivetti de França, Marco Virgolin, Michael Kommenda, Maimuna S. Majumder, Miles D. Cranmer, Guilherme Espada, Leon Ingelse, Alcides Fonseca, Mikel Landajuela, Brenden K. Petersen, Ruben Glatt, T. Nathan Mundhenk, Chak Shing Lee, Jacob D. Hochhalter, David L. Randall, P. Kamienny, Hengzhe Zhang, Grant Dick, Alessandro Simon, Bogdan Burlacu, Jaan Kasak, Meera Vieira Machado, Casper Wilstrup, William G. La Cava

IEEE Trans. Evol. Comput., August, 2025

Patho-AgenticRAG: Towards Multimodal Agentic Retrieval-Augmented Generation for Pathology VLMs via Reinforcement Learning.

Wenchuan Zhang, Jingru Guo, Hengzhe Zhang, Penghao Zhang, Jie Chen, Shuwan Zhang, Zhang Zhang, Yuhao Yi, Hong Bu

CoRR, August, 2025

LLM-Meta-SR: Learning to Evolve Selection Operators for Symbolic Regression.

Hengzhe Zhang, Qi Chen, Bing Xue, Mengjie Zhang

CoRR, May, 2025

Call for Action: towards the next generation of symbolic regression benchmark.

Guilherme Seidyo Imai Aldeia, Hengzhe Zhang, Geoffrey F. Bomarito, Miles D. Cranmer, Alcides Fonseca, Bogdan Burlacu, William G. La Cava, Fabrício Olivetti de França

CoRR, May, 2025

RAG-SR: Retrieval-Augmented Generation for Neural Symbolic Regression.

Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Micro-step Time-Series Regression: Insights from System Identification Using Symbolic Regression.

Hengzhe Zhang, Alberto Tonda, Qi Chen, Bing Xue, Evelyne Lutton, Mengjie Zhang

Proceedings of the Genetic Programming - 28th European Conference, 2025

A General Feature-Informed Crossover for Two-Stage Feature Selection in Symbolic Regression.

Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

Proceedings of the IEEE Congress on Evolutionary Computation, 2025

2024

A Semantic-Based Hoist Mutation Operator for Evolutionary Feature Construction in Regression.

Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

IEEE Trans. Evol. Comput., December, 2024

SR-Forest: A Genetic Programming-Based Heterogeneous Ensemble Learning Method.

Hengzhe Zhang, Aimin Zhou, Qi Chen, Bing Xue, Mengjie Zhang

IEEE Trans. Evol. Comput., October, 2024

Modular Multitree Genetic Programming for Evolutionary Feature Construction for Regression.

Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

IEEE Trans. Evol. Comput., October, 2024

A geometric semantic macro-crossover operator for evolutionary feature construction in regression.

Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

Genet. Program. Evolvable Mach., June, 2024

Sharpness-Aware Minimization for Evolutionary Feature Construction in Regression.

Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

CoRR, 2024

P-Mixup: Improving Generalization Performance of Evolutionary Feature Construction with Pessimistic Vicinal Risk Minimization.

Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

A Semantic-based Hoist Mutation Operator for Evolutionary Feature Construction in Regression [Hot off the Press].

Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Bias-Variance Decomposition: An Effective Tool to Improve Generalization of Genetic Programming-based Evolutionary Feature Construction for Regression.

Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

Improving Generalization of Evolutionary Feature Construction with Minimal Complexity Knee Points in Regression.

Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

Proceedings of the Genetic Programming - 27th European Conference, 2024

2023

MAP-Elites for Genetic Programming-Based Ensemble Learning: An Interactive Approach [AI-eXplained].

Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

IEEE Comput. Intell. Mag., November, 2023

Automatically Choosing Selection Operator Based on Semantic Information in Evolutionary Feature Construction.

Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

Proceedings of the PRICAI 2023: Trends in Artificial Intelligence, 2023

Genetic Programming-based Evolutionary Feature Construction for Heterogeneous Ensemble Learning [Hot of the Press].

Hengzhe Zhang, Aimin Zhou, Qi Chen, Bing Xue, Mengjie Zhang

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

A Double Lexicase Selection Operator for Bloat Control in Evolutionary Feature Construction for Regression.

Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

MAP-Elites with Cosine-Similarity for Evolutionary Ensemble Learning.

Hengzhe Zhang, Qi Chen, Alberto Tonda, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang

Proceedings of the Genetic Programming - 26th European Conference, 2023

BertNet: Harvesting Knowledge Graphs with Arbitrary Relations from Pretrained Language Models.

Shibo Hao, Bowen Tan, Kaiwen Tang, Bin Ni, Xiyan Shao, Hengzhe Zhang, Eric P. Xing, Zhiting Hu

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

An Evolutionary Forest for Regression.

Hengzhe Zhang, Aimin Zhou, Hu Zhang

IEEE Trans. Evol. Comput., 2022

PS-Tree: A piecewise symbolic regression tree.

Hengzhe Zhang, Aimin Zhou, Hong Qian, Hu Zhang

Swarm Evol. Comput., 2022

BertNet: Harvesting Knowledge Graphs from Pretrained Language Models.

Shibo Hao, Bowen Tan, Kaiwen Tang, Hengzhe Zhang, Eric P. Xing, Zhiting Hu

CoRR, 2022

2021

RL-GEP: Symbolic Regression via Gene Expression Programming and Reinforcement Learning.

Hengzhe Zhang, Aimin Zhou

Proceedings of the International Joint Conference on Neural Networks, 2021

2020

Information Fusion in Offspring Generation: A Case Study in Gene Expression Programming.

Tonglin Liu, Hengzhe Zhang, Hu Zhang, Aimin Zhou

IEEE Access, 2020

A Multi-metric Selection Strategy for Evolutionary Symbolic Regression.

Hu Zhang, Hengzhe Zhang, Aimin Zhou

Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020