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Zhongmin Yan

2 accepted papers

2026

Learning Efficient and Interpretable Multi-Agent Communication

ICLR 2026poster

Effective communication is crucial for multi-agent cooperation in partially observable environments. However, a fundamental trilemma exists among task performance, communication efficiency, and human interpretability. To resolve this, we propose a multi-agent communication framework via $\textbf{G}$…

Cited by 0SourceScholar
2021

Few-Shot Partial-Label Learning

IJCAI 2021poster

Partial-label learning (PLL) generally focuses on inducing a noise-tolerant multi-class classifier by training on overly-annotated samples, each of which is annotated with a set of labels, but only one is the valid label. A basic promise of existing PLL solutions is that there are sufficient partial…

Cited by 4SourcePDFScholar