Meng, Zaiqiao

Revisiting Parameter-Efficient Tuning: Are We Really There Yet?

Chen, G., Liu, F., Meng, Z., & Liang, S. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 60

A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems

Fang, J., Peng, Y., Zhang, X., Wang, Y., Yi, X., Zhang, G., Xu, Y., Wu, B., Liu, S., Li, Z., et al. (2025) · arXiv

Evolutionary Algorithms and ApplicationsAI-based Problem Solving and Planning

Cited by 6

EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery

Lyu, Y., Zhang, X., Zhao, Y., Papakostas, K., Yi, X., Guo, S., Hu, W., Piotrowski, J., Kaliski, J., Urbani, J., et al. (2026) · arXiv

Artificial Intelligence ApplicationsEvolutionary Algorithms and Applications

Cited by 2

Automated Chest X-ray Report Generation Remains Unsolved.

Zhang, X., Acosta, J. N., Yang, X., Adithan, S., Luo, L., Zhou, H.-Y., Miller, J., Huang, O., Zhou, Z., Hamamci, I. E., et al. (2025) · Biocomputing 2026

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 2

EvoAgentX: An Automated Framework for Evolving Agentic Workflows

Wang, Y., Liu, S., Fang, J., & Meng, Z. (2025) · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

Multi-Agent Systems and NegotiationEvolutionary Algorithms and Applications

Cited by 1