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Medical Large Language Models
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Mën-mën yu feeñ ci misaali làkk yu mag
Mën-mën yuy feeñ mooy mën-mën yiy feeñ ci saasi ci misaali làkk yu mag yi ginaaw bi ñu weesee benn eskaal, doonte misaal yu ndaw yi wone wuñu leen benn màndarga.
Déglul tegtal biiIA-nettali · ~2 min
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Résumé
They matter because they make capabilities hard to predict from small-scale experiments.
Plongeur bu xóot
Ñu siiwal ko ci benn téere bu Wei ak ay naataangoom bind ci 2022, génne gi dafay wax ci liggéey yu performance yi di des ci wetu saas ngir model yu gëna ndaw ba noppi di tëb bu baax su model bi jéggee benn dayo ci parametre yi, done yi, wala calcul yi. Ay misaal yuñ joxe bokkuna ci xayma yu bari, yenn tegtali xalaat, ak topp tegtal yu bees. Li ci gënoon fës mooy ñàkka wéy: mën mën bi nekkul woon luy yokk ndànk, dafa melni lu amul ba noppi nekk. Benn toppu bu 2023 bu Schaeffer ak ay naataangoom wax ni yenn feeñte yi bokk nañu ci ay mbiri natt, ndax ay metrik yu dëgër yu mel ni exact-match dañuy juum ci ay tëb yu gaaw yuy nuru lu nooy ci suufu poñ yu gëna woyof. Werante bi soppali na anam wi gëstukat yi di joxee rapoor ci resultaa yi ak tànneefi evaluation yi.
Doxal ci àdduna dëgg
Modèle yu mag yiy saafara jafe-jafe baat yu bari te version yu ndaw yi tontu ci niveau chance.
Benn model buy jekki saa rek topp ay tegtal yu jafee xam, yu kenn musul gis ginaaw bimu jàllee benn ëttu balans.
Caden-de-pensée biy ñaax nit ñi ñu xalaat ludul su model yi yeggee ci dayo bu doy.
Gëstukat yi dañu defaraat ap tëb bu 'ci saasi' ak poñ yu xaaj ci kredi ba noppi gis courbe bu neex.
Ëlëgu Mën-mën yiy Feeñ ci Royuwaayi Lakk yu Yaatu
Leegi gëstukat yi dañuy boole njàngum scaling ak metrics yu bari ngir tàqale coppite fase yu dëggu yi ak artifact yi, ba noppi ñuy saytu ban kàttan mooy yegsi ci scale bi. Li gëna am solo mooy gëna mëna xam luy am ci kaaraange, ndax mën nañu am luñu xamul luy am risk. Xaarandil liggéey bu gëna bari ci yooni scaling yiy wax luy waaja am ci kanam, boole ci jëmmal benchmark bu jaar yoon suko defee ñu wax ni 'feññ' dafay wane doxalinu model bi te baña nekk benn quirk ci natt gi.
Teg ko ci jëf
Lu tax mu am solo
- Gaawaay ak yaatuwaay. Liggéeyukaay yi ci làkk yi mën nañu gëna gaaw te duñu yàq deggoo gi.
- Dugg ak yegg. Dafay yaatal jëfandikoo gi ci làkk yi ak ci anam yi ñuy jokkoo.
- dogal yu gëna leer. Ekip yi mën nañu gëna yàgg ci àtte ci jamono ji otomatisation di liggéey ci baamtu.
Moytul
- Lépp lu jaarul yoon mën na dugg ci rapoor yi, jàppale ci liggéey bi, wala ci njariñu gëstu bi.
- Sensibilite bu gaaw mën na jur njariñ yu wuute ci laajte yu noonu mel.
- Done yu am solo mën nañu feeñ sudee seytu jëfandikoo gi néew doole.
Jéego yi ci topp
- Mandargal formaa génne gi, melokaan bi, ak standard kalite yi laata ngay dugal ko.
- Tontu yu am solo ak balluwaay yu wóor saa yu dëggu bi di am solo.
- Fexeel am barabu xool nit ñi ngir am njariñ yu am solo.
- Toppal anami gacce yi ak di faral di tàggataat ay laaj wala def-liggéey.
Weyal di banneexu
Bulletin bu amul fayda
Jàngal xibaar AI bu bes
Ñatti jaar-jaari IA yuñ firndeel bis bu nekk ci ayu-bis bi, ñu bind leen ci Àngle bu leer. Gratis ba fàww, amul yëgle.
Benn email bis bu nekk ci ayu-bis bi. Benn klik nga dindi abonemaa bi. Dunu musa jaay wala séddoo sa adres.
Nattal sa bopp
Take the Emergent Abilities of Large Language Models quiz
Feedback ci saasi ci bépp tontu, ak sertifikaa buñ mëna séddoo ak ID buñ mëna saytu soo jàllee ci njàng mi.
Jàppale njàngum IA te doo fay. AI Understanding mbootaay la buy def te Yàlla tax — amul yëgle, amul paywall, musul am. Defal ab sarax
Laaj yi ñuy faral di laaj
What is Emergent Abilities of Large Language Models?
Mën-mën yuy feeñ mooy mën-mën yiy feeñ ci saasi ci misaali làkk yu mag yi ginaaw bi ñu weesee benn eskaal, doonte misaal yu ndaw yi wone wuñu leen benn màndarga. Dañu am solo ndax dañu tax ñu baña mëna wax luy am ci jàngat yu ndaw.
What did early emergence reports describe?
The cited work described apparently sharp capability changes for some tasks.
What alternative did Schaeffer and colleagues argue?
The follow-up argues nonlinear or discontinuous metrics can create apparent abrupt jumps.
Why can exact-match scoring make a gradual skill look abrupt?
The study explains that all-or-nothing metrics can exaggerate a discontinuity.
What might happen if partial-credit or continuous metrics are used?
The paper reports metric changes can reveal smoother performance trends.
What is needed before concluding a new ability appeared at a scale threshold?
The research debate emphasizes metric choice and better statistics.
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