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Takarda tana ba da shawarar gwajin mataki biyu don zaɓar LLMs ƙarƙashin ƙimayar rashin tabbas

Wani sabon bugu yana ba da hujjar cewa wasu lokuta kamfanoni na iya tabbatar da mafi kyawun aiki na manyan yare don yin aiki maimaituwa koda kuwa ƙiyasin ingancin ƙira sun kasance marasa tabbas. Yana ba da shawarar gwajin warwarewa biyu da hanyar tattara shaida da ake kira CASE.

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Source-provided image accompanying Paper proposes a two-step test for choosing LLMs under uncertain evaluations
Takardun tushe na farkoAn rubuta tushen tushe
Mawallafi
arxiv.org
Tushen hanyar haɗin gwiwa
arxiv.orghttps://arxiv.org/abs/2608.29560
Nau'in tushe
Takardun farko - sanarwar hukuma, takarda, yin rajista, ko shafi na farko da muka karanta kai tsaye.
MaganaFahimtar wannan a cikin daƙiƙa 60

Fara a nan

Mabuɗin sharuddan

Babban Samfurin Harshe (LLM)
Samfurin harshe da aka horar akan babban haɗin gwiwar rubutu don samarwa da tantance rubutu.
Karfi
Ƙarfin samfurin don kula da aiki a ƙarƙashin amo, canje-canje, ko abubuwan shigar gaba.
Alamar alama
Daidaitaccen gwaji ko saitin bayanai da aka yi amfani da shi don aunawa da kwatanta aikin ƙira.
Gwada kankaChatGPT & LLMs Tambayoyi

Me ya faru

Masu bincike Hamed Khosravi da Xiaoming Huo sun ba da shawarar tsari don rarraba nauyin aiki a tsakanin manyan nau'ikan harshe lokacin da ƙungiya ke da ƙayyadaddun tsarin kasafin AI amma bai cika ko shaidar da ba ta da tabbas game da ingancin samfurin. Takardar ta raba matsalar inganta ɗawainiya daga matsala mai wuyar ƙimayar yadda kowane ƙirar ke aiki akan kowane nau'in aiki.

Rubutun arXiv ya lissafa takarda kamar yadda aka gabatar a kan 30 Agusta 2026. Batunsa shine kamfani wanda ke zabar wane nau'in harshe mai girma ya kamata ya kula da kowane aiki mai maimaitawa yayin aiki a ƙarƙashin ƙayyadaddun kasafin kuɗi na fasaha na wucin gadi. Marubutan sun bayyana matsalar rabon a matsayin mai sauƙi da zarar an sami ingantaccen tebur mai inganci: kowane shigarwar tebur zai wakilci yadda wani samfurin ke aiki akan wani nau'in aiki. Hujjarsu ita ce, gina wannan teburi shine abu mai wuyar gaske, ba warware matsalar aikin da aka samu ba.

Marubutan sun gano tushen rashin tabbas guda biyu. Na farko, sau da yawa ba a kwatanta samfura akan aiki ɗaya ba, wanda ke sa kwatancen aikin kai tsaye da wahala. Na biyu, makin kima da aka yi rikodin na iya auna wakili maimakon sakamakon da kamfani ke ƙima. Ƙididdigar ta ce hanyoyin haddasawa da rashin bin doka na iya magance batun farko yayin da har yanzu ya dogara da wakili, yayin da hanyoyin tantancewa na iya magance na biyu ba tare da kammala yanke shawara ba. Takardar ta ci gaba da cewa sayan ƙarin kima ba lallai ba ne ya warware rashin tabbas game da yadda ake samar da maki, saboda bazuwar yana canza abin da ake buƙatun maimakon ma'anar ma'anar kanta.

Gwajin shawarar da aka gabatar yana tambaya ko aikin nauyin aiki ɗaya ya kasance mafi kyau a cikin kowane tebur mai inganci daidai da shaidar da ake da ita. Don kafaffen saitin kasafin kuɗi, marubutan sun bayyana ainihin takardar shedar warwarewa guda biyu: haɓakawa ɗaya yana amfani da kiyasin tebur mai inganci, na biyu kuma yana amfani da tebur mafi ƙarancin inganci. Yarjejeniyar tsakanin mafita guda biyu ta tabbatar da aiki a cikin tsarin takarda. Rashin jituwa yana gano nau'i-nau'i-nau'i-nauyin aiki wanda ƙarin shaida zai iya canza shawarar.

Takardar kuma tana ba da shawarar CASE, ko gwajin gwaji na jeri mai tasiri. Hanyar tana jagorantar ƙarin kimantawa zuwa nau'i-nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i nau'i) nau'i-nau'i-aiki) wanda ke da mahimmanci ga yanke shawara mara tabbas, sannan ta maimaita gwajin ƙarfin yayin da sababbin shaida ta zo. Rahoton abstract yana haifar da sakamakon bayanan samarwa da ayyukan software da aka biya, amma baya bayyana cikakkun bayanai a cikin rubutun tushen don tantance ma'auni ko ƙira na waɗannan gwaje-gwajen. Ya ce gyara aikin daidai yana barin mafi yawan hasara a cikin saitin log-production, cewa sake-ƙimar bazuwar bai kawar da matsalar ma'aunin ba, kuma kasancewar shaidar sau da yawa ta kasa tantance wani aiki na musamman.

Bayanan tushe: arxiv.org ↗

Me ya sa yake da mahimmanci

Babban da'awar takarda ita ce mafi kyawun ma'auni na iya haifar da ƙima fiye da sake inganta yanke shawara da aka gina akan ƙididdiga masu rauni. Idan an inganta fiye da gwaje-gwajen da aka ruwaito, tsarin zai iya taimaka wa ƙungiyoyi su yanke shawara lokacin da shaidarsu ta yi ƙarfi don ƙaddamar da aikin ƙira da kuma lokacin da aka ba da garantin ƙarin gwaji.

Gudunmawar a aikace ita ce canji a cikin abin da ake buƙatar ƙungiya don ingantawa. Ƙungiya zaɓen samfuri na iya mai da hankali kan nemo mafi kyawun aikin lissafi don makin makinta na yanzu. Wannan takarda ta ce aikin na iya zama ƙasa da mahimmanci fiye da tantance ko waɗannan ƙididdigan sun kasance amintacce kuma sun dace da ainihin manufar ƙungiyar. Wannan bambance-bambancen yana da mahimmanci lokacin da samfurin ya bayyana mai ƙarfi akan ma'auni amma yana yin daban akan aikin da ke haifar da farashi, kudaden shiga, jinkiri, ko haɗari.

Takaddun shaida da aka tsara zai iya ba da ƙayyadadden ƙa'idar tsayawa. Yarjejeniya tsakanin ƙayyadaddun bayani-tebur da mafi ƙarancin-fifa-tebur mafita zai nuna cewa wannan aikin ya tsira daga ƙayyadadden ƙayyadaddun rashin tabbas na takarda. Rashin jituwa ba zai gano samfurin nasara ba, amma zai taƙaita rashin tabbas ga nau'i-nau'i masu nauyin aiki na musamman. A ka'ida, hakan na iya sanya kashe kuɗin kimantawa ya fi niyya kuma ya hana ƙungiyoyi tattara bayanai masu yawa waɗanda ba za su iya shafar shawarar turawa ba.

Gwaje-gwajen da aka ruwaito sun nuna wani darasi mai mahimmancin aiki, kodayake tushen ba shi da girman tasiri. A kan ayyukan software da aka biya, marubutan sun ce samun ingantattun bayanai game da ingancin samfurin ya samar da ƙarin tanadi fiye da ƙara inganta aikin ta amfani da ƙididdiga iri ɗaya. Idan wannan sakamakon ya zama gama gari, ƙungiyoyi za su iya amfana daga saka hannun jari a takamaiman ma'auni, ingantaccen sakamako, da gwaje-gwaje masu kama da juna kafin yanke shawarwari masu inganci. Sakamakon bai tabbatar da cewa samfurin ɗaya ya fi girma ba; ya shafi darajar bayanai a cikin matsalar rabon kasafin kuɗi.

Sakamakon binciken ya kuma nuna iyakacin kwatancen salon jagora. Maki yana da amfani kawai gwargwadon yadda yake bibiyar sakamakon da ƙungiyar ta damu da shi, kuma kwatancen suna da wahala lokacin da aka gwada samfura akan ayyuka daban-daban. Don haka takardar ta zayyana zaɓin ƙira azaman ma'auni da matsalar yanke shawara maimakon motsa jiki mai sauƙi. Wannan ƙirƙira ya dace da kamfanoni masu amfani da ƙira da yawa, amma tushen bai tabbatar da nawa ƙoƙarin aiwatar da CASE zai buƙaci ba ko kuma tunaninsa ya dace da tsarin saye da turawa na gaske.

Interactive Mechanism

Ingantacciyar hanyar sadarwa: Yadda A zahiri yake Aiki

Bincika fasahar da ke bayan wannan ci gaban ta hanyar mu'amala.

Thinking Budget (Test-Time Tokens):1,024 tokens
Complex Accuracy79%Math & Code Logic
Latency3.2sTime to first full output
Inference Cost$0.0092Per query estimated
Reasoning StyleStep VerificationInternal chain depth
Active Thinking Trace:
1Deconstruct user problem into formal constraints
2Propose candidate hypotheses & step-by-step calculation
3Self-correction: Backtrack and refute subtle edge cases
4Exhaustive consistency check & final output synthesis
Core takeaway: Test-time compute fundamentally changes AI economics. Instead of only scaling during pre-training, giving reasoning models more tokens at inference time allows them to systematically solve PhD-level STEM problems.
Duba ra'ayi na hulɗa+10 Points
ChatGPT & LLMs Quiz

What is a common training objective for an autoregressive language model?

Abin kallo na gaba

Aikin faifan arXiv ne, kuma tushen baya samar da girman samfuri, sunaye na ƙididdigewa, ƙidayar ɗawainiya, ƙididdige farashi, girman sakamako, lamba, ko ingantaccen aiki mai zaman kansa. Ya kamata ƙarin bincike ya bincika ko takardar shaidar da aka tsara da kuma hanyar CASE ta riƙe nauyin ayyuka daban-daban, masu samar da samfuri, tsarin farashi, da ma'aunin ƙima.

Babban abin da ba a san shi ba shine shaidar da ke bayan rahoton samarwa da sakamakon aikin-software da aka biya. Rubutun tushen bai faɗi adadin buƙatun, nauyin aiki, samfuri, ko kimantawa da aka haɗa ba; yadda aka bayyana kasafin AI; wanda aka auna farashi da sakamakon; ko girman adadin ajiyar da aka ruwaito da ragowar asarar da aka yi. Idan ba tare da waɗannan cikakkun bayanai ba, alkiblar abubuwan da aka gano a bayyane take daga maƙasudin, amma girman aikinsu ba haka yake ba.

Ya kamata ƙarin bita ya gwada zato a bayan tsarin rashin tabbas da tebur mafi ƙarancin fa'ida. Takaddun shaida daidai ne don ƙayyadaddun matsalar kasafin kuɗi kamar yadda aka bayyana, amma fa'idar ta ya dogara da ko saitin tebur mai inganci da gaske yana ɗaukar rashin tabbas da ƙungiyar turawa ke fuskanta. Idan an cire mahimman nau'ikan canjin rarraba, canza nauyin aiki, sabuntawar ƙira, ko canje-canjen farashi, yarjejeniya tsakanin warwarewar biyu na iya samar da ƙarancin tabbaci fiye da sakamakon da aka nuna.

Gwaje-gwajen da aka yi niyya kuma suna ba da tabbacin bincike. CASE an yi niyya don zaɓar kimantawa waɗanda za su iya canza shawarar rarrabawa, amma tushen baya yin bayanin ƙa'idar gwaji, dokar dakatarwa, garantin ƙididdiga, ko kariya daga yanke hukunci daga abubuwan lura kaɗan. Masu bincike da masu aiki ya kamata su nemi cikakkun hanyoyin takarda, fitar da bayanai ko lambar, nazarin hankali, da kwatance tare da dabarun kimantawa masu sauƙi.

A ƙarshe, ya kamata a kula da aikin azaman preprint maimakon ƙa'idar masana'antu mai zaman kanta. Madogarar ta gano ainihin takaddun shaida kuma tana ba da rahoton da'awar gwaji, amma ba ta ambaci sake dubawar takwarorinsu ko kwafi na waje ba. Mahimman tambayoyin biyo baya sun haɗa da ko hanyar tana aiki don abubuwan da ba software ba, ko tana sarrafa maƙasudi da yawa kamar inganci, jinkiri, da aminci, da kuma ko ƙungiyoyi za su iya fassara makin wakili zuwa sakamakon waɗanda ke da ma'auni kuma masu dacewa da yanke shawara.

Jagorori masu alaƙa & tambayoyin tambayoyi

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