Author

Liang Dong

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2026

Interpretable Reaction–Diffusion Learning for Molecular Communication via Graph Kolmogorov–Arnold Networks

Molecular communication (MC) lets biological cells coordinate collective behaviors through diffusion-mediated signaling molecules that couple intracellular reaction kinetics across a spatial graph. Existing graph neural networks are accurate but opaque, while classical reaction–diffusion models require an explicit kine...

Liang Dong · IEEE Transactions on Molecul... · 0 citations

2026

Achievable Rates of Coded NOMA With Finite-Alphabet Inputs and Suboptimal Detection

Power-domain non-orthogonal multiple access (NOMA) is conventionally analyzed under Gaussian input assumptions, where successive interference cancellation (SIC) achieves the multiple-access channel (MAC) capacity region. Practical systems, however, employ finite-alphabet modulations and suboptimal detectors, which resh...

Liang Dong · IEEE Transactions on Communi... · 1 citation

Jul 2026

When Unlearning Fails: Reliable Data Deletion under Post-Training in Agent Networks

Self-improving federated agent networks keep training after deployment by collecting new trajectories with the current policy and feeding them back into later rounds. This closed loop makes unlearning harder than a one-time model repair. When a data owner requests deletion, the target data may have already shaped later...

Zihao Ding, Jun Huang, Liang Dong · arXiv.org · 0 citations