Centrality measures are widely used to rank nodes in networked data, but fairness interventions for graph centrality typically target global score mass or modify the centrality operator rather than controlling who appears in the displayed top-k ranking. We study this top-k setting for Katz centrality. Given a target gr...
Ivan Qin, Prudence Wong, Lutz Oettershagen· 0 citations
Writing and communication are increasingly mediated by large language models (LLMs) that are being used to draft, revise and polish text. Although such assistance can improve clarity and help authors meet institutional expectations, widespread reliance on shared models may reduce population-level variation in linguisti...
Suhas Thejaswi, Juhi Kulshreshta, Lutz Oettershagen· arXiv.org· 0 citations
Empirical results show that FML enforces group-level fairness, while the graph-native variant substantially improves scalability and achieves competitive activation cost.
Lutz Oettershagen, Othon Michail· Neural Information Processin...· 1 citation
This work introduces FALCON (Filtration-based hypergrAph aLignment via Cross-scale Optimal traNsport), an unsupervised optimal-transport framework for hypergraph alignment that constructs a filtration-induced sequence of clique-based co-occurrence dissimilarity matrices and jointly aligns all levels through one shared...
Lutz Oettershagen, Honglian Wang, A. Gionis· 0 citations
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