Has used anLLM tosummarizeresearchpapersHasparticipated ina hackathonfocused on AIor LLMsHas experiencewith low-resourcelanguages inNLPHasattended anICMLconferencebeforeCanrecommenda good AI ortech relatedpodcastHas collaboratedon a researchpaper withsomeone from adifferent continentCan explain thedifferencebetween causaland maskedlanguagemodelsHaspublishedresearch onmultilingualLLMsHas presenteda paper onnaturallanguagegenerationIs interestedin the ethicalimplicationsof generativeAIHas used agenerative AImodel for anon-academicpurposeHasexperiencewith fine-tuning a pre-trained LLMHas used agenerative AImodel tocreate art ormusicIs excitedabout thepotential ofLLMs ineducationHas apreferred AIresearch toolthey canrecommendHassuccessfullydebugged acomplexLLMHas traveledinternationallyto attend thisconferenceCan namethreedifferent LLMarchitecturesHascontributedto an open-source AIprojectIs currentlyworking on aprojectinvolving cross-lingual transferlearningKnows atleast threeprogramminglanguagesIs optimisticabout thefuture ofhuman-AIcollaborationIs familiarwith theconcept ofpromptengineeringHas learneda newlanguage inthe last yearHas used anLLM tosummarizeresearchpapersHasparticipated ina hackathonfocused on AIor LLMsHas experiencewith low-resourcelanguages inNLPHasattended anICMLconferencebeforeCanrecommenda good AI ortech relatedpodcastHas collaboratedon a researchpaper withsomeone from adifferent continentCan explain thedifferencebetween causaland maskedlanguagemodelsHaspublishedresearch onmultilingualLLMsHas presenteda paper onnaturallanguagegenerationIs interestedin the ethicalimplicationsof generativeAIHas used agenerative AImodel for anon-academicpurposeHasexperiencewith fine-tuning a pre-trained LLMHas used agenerative AImodel tocreate art ormusicIs excitedabout thepotential ofLLMs ineducationHas apreferred AIresearch toolthey canrecommendHassuccessfullydebugged acomplexLLMHas traveledinternationallyto attend thisconferenceCan namethreedifferent LLMarchitecturesHascontributedto an open-source AIprojectIs currentlyworking on aprojectinvolving cross-lingual transferlearningKnows atleast threeprogramminglanguagesIs optimisticabout thefuture ofhuman-AIcollaborationIs familiarwith theconcept ofpromptengineeringHas learneda newlanguage inthe last year

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