Has used anLLM tosummarizeresearchpapersIs excitedabout thepotential ofLLMs ineducationIs interestedin the ethicalimplicationsof generativeAIHas experiencewith low-resourcelanguages inNLPHas used anLLM in alanguageother thanenglishHas presenteda paper onnaturallanguagegenerationKnows atleast threeprogramminglanguagesHas used agenerative AImodel for anon-academicpurposeHas traveledinternationallyto attend thisconferenceHas learneda newlanguage inthe last yearHas collaboratedon a researchpaper withsomeone from adifferent continentHasattended anICMLconferencebeforeHasexperiencewith fine-tuning a pre-trained LLMIs familiarwith theconcept ofpromptengineeringCanrecommenda good AI ortech relatedpodcastHassuccessfullydebugged acomplexLLMHas used agenerative AImodel tocreate art ormusicHasparticipated ina hackathonfocused on AIor LLMsIs optimisticabout thefuture ofhuman-AIcollaborationHaspublishedresearch onmultilingualLLMsHas apreferred AIresearch toolthey canrecommendCan explain thedifferencebetween causaland maskedlanguagemodelsCan namethreedifferent LLMarchitecturesHascontributedto an open-source AIprojectHas used anLLM tosummarizeresearchpapersIs excitedabout thepotential ofLLMs ineducationIs interestedin the ethicalimplicationsof generativeAIHas experiencewith low-resourcelanguages inNLPHas used anLLM in alanguageother thanenglishHas presenteda paper onnaturallanguagegenerationKnows atleast threeprogramminglanguagesHas used agenerative AImodel for anon-academicpurposeHas traveledinternationallyto attend thisconferenceHas learneda newlanguage inthe last yearHas collaboratedon a researchpaper withsomeone from adifferent continentHasattended anICMLconferencebeforeHasexperiencewith fine-tuning a pre-trained LLMIs familiarwith theconcept ofpromptengineeringCanrecommenda good AI ortech relatedpodcastHassuccessfullydebugged acomplexLLMHas used agenerative AImodel tocreate art ormusicHasparticipated ina hackathonfocused on AIor LLMsIs optimisticabout thefuture ofhuman-AIcollaborationHaspublishedresearch onmultilingualLLMsHas apreferred AIresearch toolthey canrecommendCan explain thedifferencebetween causaland maskedlanguagemodelsCan namethreedifferent LLMarchitecturesHascontributedto an open-source AIproject

Human BINGO: Navigating Generative AI and LLMs Across Languages - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Has used an LLM to summarize research papers
  2. Is excited about the potential of LLMs in education
  3. Is interested in the ethical implications of generative AI
  4. Has experience with low-resource languages in NLP
  5. Has used an LLM in a language other than english
  6. Has presented a paper on natural language generation
  7. Knows at least three programming languages
  8. Has used a generative AI model for a non-academic purpose
  9. Has traveled internationally to attend this conference
  10. Has learned a new language in the last year
  11. Has collaborated on a research paper with someone from a different continent
  12. Has attended an ICML conference before
  13. Has experience with fine-tuning a pre-trained LLM
  14. Is familiar with the concept of prompt engineering
  15. Can recommend a good AI or tech related podcast
  16. Has successfully debugged a complex LLM
  17. Has used a generative AI model to create art or music
  18. Has participated in a hackathon focused on AI or LLMs
  19. Is optimistic about the future of human-AI collaboration
  20. Has published research on multilingual LLMs
  21. Has a preferred AI research tool they can recommend
  22. Can explain the difference between causal and masked language models
  23. Can name three different LLM architectures
  24. Has contributed to an open-source AI project