How challenging could it be for AI to rewrite The Great Gatsby without the letter ‘e’ and in a way that doesn’t dampen the essence of Fitzgerald’s tragic masterpiece?
For Steven Skiena, distinguished teaching professor of computer science at Stony Brook University, this question doesn’t just present an interesting writing challenge but also addresses a far bigger concern: how can LLMs effectively translate nuance, voice and style when presented with very strong language constraints?
In a paper presented at the IJCNLP-AACL conference, Skiena and his students trained a language model to write an e-less version of The Great Gatsby using AI. “The letter ‘e’ makes up roughly 12 percent of ordinary English text,” Skiena said, “and the text we produced serves as a testament of the malleability of the English language.”
Skiena and his students framed the task as a kind of translation — not from English to French or Hindi, but from ordinary English into a constrained version of itself. The challenge was to create a successful translation that can swap words and restructure sentences, but should preserve meaning, readability and flow. That is what makes the project more than a gimmick. It becomes a stress test for language models, asking them to obey a severe rule without collapsing into nonsense.
Read the full story by Ankita Nagpal on the AI Innovation Institute website.
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