Author

Moritz Piening

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Preprint Aug 2026

Alignment Matters Inside and Out in Equivariant Graph Flow Matching

Graphs are invariant under node permutations, motivating permutation-equivariant architectures in generative models. In flow matching, however, symmetry also affects the source-target coupling: one must choose both which graphs to pair and which node representatives to align. We study these two forms of alignment, term...

Moritz Piening, C. Wald · 0 citations

#machine learning Preprint Oct 2026

SOL: Measuring Gaps between Text Distributions by Double Sliced Wasserstein Metrics

Evaluating text generation requires measuring how well the generated distribution matches the data distribution. For autoregressive models, this is done by the perplexity. Diffusion and flow-based language models can only provide a likelihood bound, whose tightness differs between model families. Sample-based substitut...

Gregor Kornhardt, Moritz Piening, J. Chemseddine et al. · 0 citations

#data science Preprint Aug 2026

Gromov-Monge Flow Matching for Equivariant Graph Generation

This work develops this perspective theoretically, showing that quotient couplings can be lifted to aligned representatives without additional cost and that symmetrization yields equivariant flow-matching minimizers, including for categorical endpoint prediction.

Moritz Piening, C. Wald · 0 citations