Federated prompt learning (FPL) offers a parameter-efficient way to adapt large-scale vision-language models by collaboratively optimizing lightweight prompts across distributed clients. Existing approaches typically assume that prompts learned on heterogeneous domains can be safely aggregated. We show that this assump...
Yun-Feng Zhao, Jun Wang, Dong Wu et al.· IEEE Transactions on Pattern...· 0 citations
Single-cell spatial proteomics (SP) can reveal protein expression patterns while preserving the spatial structure of tissues, providing valuable insights into cellular functions and disease mechanisms. SP data clustering is a fundamental step in such studies, but it remains in the preliminary exploration phase, facing...
Ben-Yu Wu, Shangzhi Zhang, Yue-Qun Wang et al.· Proceedings of the 32nd ACM...· 0 citations
It is theoretically show that latent causal components and their causal relationships can be identified up to permutation equivalence by modeling synchronous sparsity in the mapping between latent components and observed variables.
Dezhi Yang, Jun Wang, C. Domeniconi et al.· Proceedings of the 32nd ACM...· 0 citations
This work introduces Evolutionary Rule Abstraction to distill generalized logic from optimization trajectories, overcoming the opacity of traditional evolution, and designs a Counterfactual Validation Module to strictly verify the causal reliability of abstracted rules.
Zhongyu Xing, Hanwen Luo, Maozu Guo et al.· Proceedings of the 32nd ACM...· 0 citations
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