> Once we have a grid, we try to fill it with words! I use simple backtracking search for that, with a timeout to stop the search on grids that are likely impossible to fill. In practice it's easy to generate a new filled grid from scratch about once every two minutes.
Have you explored other search techniques?
> After the grid is full of words, we use an LLM to generate some clues. I've iterated over many models and prompts for this.
Could you share the prompts and the models you tried?
Shameless plug: I've been interested in crossword generation for a while as well and made that toy: https://github.com/super7ramp/croiseur. No grid generation but automatic filling and clue generation. Clues are not really good, currently using gpt-4o-mini.
> Once we have a grid, we try to fill it with words! I use simple backtracking search for that, with a timeout to stop the search on grids that are likely impossible to fill. In practice it's easy to generate a new filled grid from scratch about once every two minutes.
Have you explored other search techniques?
> After the grid is full of words, we use an LLM to generate some clues. I've iterated over many models and prompts for this.
Could you share the prompts and the models you tried?
Shameless plug: I've been interested in crossword generation for a while as well and made that toy: https://github.com/super7ramp/croiseur. No grid generation but automatic filling and clue generation. Clues are not really good, currently using gpt-4o-mini.