A new approach called DiBS combines a diffusion model with a symbolic solver to improve Sudoku solving efficiency, addressing limitations of traditional heuristic and deep learning methods. This innovation significantly reduces search costs and enhances performance on challenging Sudoku puzzles, suggesting potential applications in broader constraint satisfaction problems.