recipe-generation

This paper proposes topological optimal transport-based loss functions for improving structured recipe generation in language models, addressing the limitations of standard cross-entropy training by better handling ingredient composition, quantities, and procedural accuracy. The approach shows significant improvements on recipe-specific metrics with 62% human preference over baseline methods.