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interstellarninja

interstellarninja
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updated a dataset about 7 hours ago
interstellarninja/tool-use-multiturn-reasoning
updated a dataset about 8 hours ago
interstellarninja/tool-calls-single-reasoning
reacted to jasoncorkill's post with 🔥 1 day ago
"Why did the bee get married?" "Because he found his honey!" This was the "funniest" joke out of 10'000 jokes we generated with LLMs. With 68% of respondents rating it as "funny". Original jokes are particularly hard for LLMs, as jokes are very nuanced and a lot of context is needed to understand if something is "funny". Something that can only reliably be measured using humans. LLMs are not equally good at generating jokes in every language. Generated English jokes turned out to be way funnier than the Japanese ones. 46% of English-speaking voters on average found the generated joke funny. The same statistic for other languages: Vietnamese: 44% Portuguese: 40% Arabic: 37% Japanese: 28% There is not much variance in generation quality among models for any fixed language. But still Claude Sonnet 4 slightly outperforms others in Vietnamese, Arabic and Japanese and Gemini 2.5 Flash in Portuguese and English We have release the 1 Million (!) native speaker ratings and the 10'000 jokes as a dataset for anyone to use: https://huggingface.co/datasets/Rapidata/multilingual-llm-jokes-4o-claude-gemini
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