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Hal-abuurnimoAI Understanding warbixin kooban

Waraaqu waxay soo jeedinaysaa barashada xoojinta gudaha ee codsiyada shabakadda AI ay soo saartay

Daabacaadda cusub ee arXiv waxay soo jeedinaysaa tababbarka hababka codaynta AI oo leh jawaab celin-ku-salaysan oo ku xidhan gobollo gaar ah, oo ka warbixinaya faa'iidooyinka cabbirka weyn ee jiilka app-ka ee is-dhexgalka.

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Source-provided image accompanying Paper proposes localized reinforcement learning for AI-generated web applications
Dukumeentiga isha aasaasiga ahIsha la duubay
Daabacaha
arxiv.org
Xidhiidhka isha
arxiv.orghttps://arxiv.org/abs/2608.27906
Nooca isha
Dukumeentiga aasaasiga ah - ogeysiis rasmi ah, warqad, xereyn, ama bogga xisbiga koowaad waxaan si toos ah u akhrinay.
Dulucda sheekadaKu fahan tan 60 ilbiriqsi gudahood

Halkan ka bilow

Qodobbada muhiimka ah

Xoojinta Waxbarashada
Tababbarka abaal-marintu waxay muujisaa halka wakiilku ku barto ficillada kordhinaya soo laabashada muddada dheer.
Hagaajinta
Sii wadida tababarka xogta gaarka ah ee domain-ka si loo waafajiyo qaabka horay loo tababaray ee hawl gaar ah.
Algorithm
Nidaam qeexan ama tillaabooyin uu kombuyuutarku raaco si uu u xalliyo mushkilad ama uu hawl u dhammaystiro.
Is tijaabiMoodooyinka AI Kedis La Sharaxay

Maxaa dhacay

Cilmi-baarayaashu waxay soo saareen Rubric-to-Code Credit Assignment, ama RCCA, qaab-dhismeedka xoojinta-waxbarashada ee loogu talagalay in lagu hagaajiyo nidaamyada AI ee soo saara codsiyada HTML, CSS iyo JavaScript isdhexgalka ee codsiyada luqadda dabiiciga ah. Wargeysku waxa uu sheegay in qaabkeeda Ling-RCCA-Flash uu ka sare maray nidaamyada isbarbardhigga qorayaasha ee labada bartilmaameed ee codsiga mareegta, laakiin sheegashadu waxay ka yimaadeen qoraal horudhac ah oo aan si madaxbanaan loo xaqiijin isha la keenay.

Warqadda, oo loo gudbiyay arXiv Agoosto 28, 2026, waxay wax ka qabataa nidaamyada AI ee dhisa codsiyada shabakada ee la isticmaali karo oo ka yimid tilmaamaha-luqad dabiici ah. Waxay ka soocaysaa hawshan dhamaystirka koodka caadiga ah sababtoo ah codsigu wuxuu u baahan karaa inuu buuxiyo shuruudo shaqo oo badan oo soo food saartay isticmaale hal mar. Shuruudahaasi waxay ku xirnaan karaan qaybo gaar ah oo barnaamijka la soo saaray, oo ay ku jiraan maamulayaasha dhacdada, cusboonaysiinta gobolka, jajabyada DOM iyo xulashada CSS. Qorayaashu waxay ku doodayaan in heerka sare ee Siyaasadda Qaraabada Kooxda, ama GRPO, ay hoos u dhigayso natiijooyinkan habaysan ilaa hal abaal-marin oo isku xigta ka dibna ay ku dabaqdo faa'iidada natiijada si isku mid ah dhammaan calaamadaha la soo saaray. Koontada warqadda, taasi waxay daciifinaysaa xidhiidhka ka dhexeeya guuldarrooyinka gaarka ah iyo koodka sababay.

RCCA waxaa loo qaabeeyey in ay u rogto jawaab celin hawleed heer rubi ah oo ay u beddesho calaamado tababar oo badan oo deegaan ah. Qaab-dhismeedku waxa uu dhisaa hawlo ku xeeran qoraalo shaqaynaya oo cad oo adeegsanaya abaal-marin kala sarraysa oo kala saaraya qaab-darrada qaabka, cillad-code-ka, guul-darrooyinka runtime iyo guul-darrooyinka shaqaynta. Kadibna waxa ay isku toosisaa sifooyinka qoraalka ee uu soo saaray qiimeeyaha oo leh taako kood mas'uul ka ah iyo calaamadihii iyaga abuuray. Isha la keenay ma sharaxdo naqshada saxda ah ee qiimeeyaha, -ka tilmaanta, xogta tababarka, kharashka xisaabinta ama haddii nidaamka iyo koodka la xidhiidha si guud loo heli karo. Ka dhaafidaas waa arrin sababtoo ah qiimaha dhabta ah ee meelaynta amaahda deegaanka waxay ku xiran tahay haddii sifooyinku yihiin kuwo sax ah oo deggan oo ku filan si loo hago tababarka.

Qaabka soo baxay, oo ay qorayaashu ugu yeeraan Ling-RCCA-Flash, ayaa lagu soo waramayaa inuu dhaliyay 41.25 MiniAppBench. Wargeysku wuxuu leeyahay tani waa 32.20 dhibcood ka sarreeya Ling-3.0-Flash oo wax yar ka sarreeya Claude Opus 4.5. On ArtifactsBench, moodeelka waxaa lagu soo waramayaa inuu dhaliyay 76.19, horumar dhan 4.48 marka loo eego qaabka hagaajinta wanaagsan ee ay kormeerayaan qorayaasha. Wargeysku waxa uu intaa ku daray in tani ay samaysay dhibco sare oo cusub oo hoos timaada goobta hogaanka ArtifactsBench oo ay dhaaftay dhibcaha GPT-5 ee la soo sheegay 3.64. Kuwani waa sheegashooyin lagu sameeyay qoraallada la daabacay; Isha la keenay ma bixiso ku celcelin madax-bannaan, jaantusyo faahfaahsan ama qiyaas aan la hubin.

Faahfaahinta isha: arxiv.org ↗

Maxay muhiim u tahay

Habkani wuxuu bartilmaameedsanayaa dhibaatada dhexe ee software-ka AI soo saartay: hal codsi ayaa buuxin kara shuruudaha qaar halka kuwa kale ku guuldareystaan ​​maamulayaasha dhacdooyinka maxaliga ah, cusbooneysiinta gobolka, walxaha bogga ama sharciyada qaabka. Jawaab celin sax ah oo dheeraad ah ayaa ka caawin karta tababarka in diirada la saaro koodka la xidhiidha guuldarradu halkii lagu meelayn lahaa hal abaalmarin dhammaan taxanaha la soo saaray.

Codsiyada AI-abuuray waxay inta badan ku fashilmaan siyaalo ka cidhiidhi ah barnaamijkii fashilmay. Interface-ka la sameeyay ayaa laga yaabaa inuu si sax ah u sameeyo laakiin wuxuu leeyahay badhan jaban, luminaya xaalad is dhexgalka ka dib, ka tag bogga loo baahan yahay ama ku dabaq qaab khaldan hal qayb. Aragtida dhexe ee warqadu waa in nidaamka tababarku uu awood u yeesho inuu kala saaro kiisaskaas oo uu si toos ah u barto koodka ku xiran shuruudaha fashilmay. Haddii habku u shaqeeyo sida lagu sharraxay, waxay ka dhigi kartaa xoojinta barashada faa'iido badan u leh hawlaha software halkaas oo saxnaanta lagu qaybiyo meelo badan oo kood ah oo isku xiran.

Natiijooyinka la soo sheegay ayaa suurtagal ah inay muhiim yihiin sababtoo ah warqaddu waxay ku qiimeysaa habka laba calaamadood oo abuurista codsi halkii ay soo bandhigi lahayd kaliya farsamada tababarka iyada oo aan la helin natiijooyin heer-hawleed ah. Qorayaashu waxay ku tilmaameen faa'iidooyinka la wareejin karo horumarin heer-fulin ah, iyadoo mid la soo sheegay isbarbardhigga Ling-3.0-Flash ee MiniAppBench iyo mid kale oo ka dhan ah qaabka SFT ee ArtifactsBench. Isku-dhafkaas wuxuu soo jeedinayaa qaab-dhismeedka jawaab-celinta ee la soo jeediyay inay saameyn karto labadaba waxqabadka moodeelka iyo awoodda guud ee goobaha qiimeynta. Si kastaba ha ahaatee, buundooyinka bartilmaameedka oo keliya ma sheegaan in codsiyada la soo saaray ay ku tiirsan yihiin isticmaalayaasha, ay ilaalin karaan horumariyeyaasha ama badbaadada in la geeyo.

Shaqadu waxay sidoo kale muujinaysaa jihada ballaadhan ee tababarka AI: ku beddelashada calaamadaha guusha-ama guul-darrida oo leh jawaab celin ka tarjumaysa qaabka hawsha. Nidaamyada kood-samaynta, kaas oo ugu dambayntii taageeri kara sixitaanka la beegsaday ee cilladaha shaqada. Isha, si kastaba ha ahaatee, waxay taageertaa gabagabo kooban oo kaliya: qorayaashu waxay soo jeedinayaan RCCA waxayna ka warbixiyaan hagaajinta bartilmaameedka qaabkooda. Ma tusinayso in dawku wanaajinayo nooc kasta oo codayn ah, hoos u dhigaya kharashaadka tababarka, la shaqaynta jawaab celinta dadka, ama u wareejinta mashaariicda software-ka weyn. Xaqiiqda ah in shaqadu tahay daabacaad hore oo arXiv ah waxay sidoo kale ka dhigan tahay sheegashooyinkeeda waa in loola dhaqmo si ku meel gaar ah ilaa hababka iyo natiijooyinka ay helayaan baaritaan dheeraad ah.

Interactive Mechanism

Farsamaynta Is-dhexgalka: Sida Dhabta Ay U Shaqeyso

U baadh tignoolajiyada hoose ee ka dambeeya horumarkan si isdhexgal leh.

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.
Hubinta Fikradda Is-dhexgalka+10 Points
AI Models Explained Quiz

Which component of an AI application is the machine-learning model itself?

Maxaa la daawan doona xiga

Waxyaabaha ugu muhiimsan ee aan la garanayn ayaa ah sida RCCA loo hirgeliyay, sida qiimeeyayaashu ay u nisbeeyeen guuldarrooyinka koodka, inta ay le'eg yihiin iyo in ay matalaan bartilmaameedyadu, iyo haddii guulaha la soo sheegay ay ka baxsan yihiin goobaha imtixaannada qorayaasha. Isha ma dejiso isku halaynta wax soo saarka, helitaanka, dib u soo saarista ama waxqabadka codsiyada adduunka dhabta ah.

Mudnaanta koowaad waa tafaasiisha habka. Bogga arXiv ee la keenay waxa uu ka kooban yahay aan la taaban karin laakiin maaha caddaynta loo baahan yahay si loo qiimeeyo isbarbardhigga si buuxda. Akhristayaashu waxay u baahan doonaan borotokoolka qiimaynta oo dhammaystiran, tirinta hawsha bar-tilmaameedka, qeexitaannada buundooyinka, noocyada aasaasiga ah, degdegga ama dhismaha hawsha, kala duwanaanshaha soo noqnoqda iyo daraasadaha baabiinta. Gaar ahaan, waxaa muhiim ah in la ogaado inta ka mid ah hagaajinta la soo sheegay ee ka timi habka credit-signment laftiisa, inta ay ka imanayso naqshadaynta ama qiimeeyaha, iyo in isla habka qiimaynta si cadaalad ah loogu dabaqay dhammaan moodooyinka isbarbardhigga.

Dib u soo saaridu waxay ku xirnaan doontaa helitaanka moodeelka, xeerka tababarka, qeexitaannada qoraalka, hirgelinta qiimaynta iyo agabka cabbirka. Isha ma cadda in Ling-RCCA-Flash la heli karo, in hawlaha bartilmaameedku ay yihiin dad caam ah, ama in qaabka lagu qiimeeyay xaalado la mid ah Claude Opus 4.5 iyo GPT-5. Sidoo kale ma tilmaamayso muhiimada tirakoobka ee farqiga dhibcaha. Faa'iidada 3.64-dhibcood ee la soo sheegay in ka badan GPT-5 iyo booska ugu sarreeya ee ArtifactsBench ayaa sidaas darteed weli ah natiijooyinka qoraaga laga soo sheegay halkii laga heli lahaa natiijooyin madax-bannaan.

Imtixaan wax ku ool ah ayaa noqon doona haddii faa'iidooyinka ay ku sii jiraan codsiyada leh shuruudo aan caddayn, is-dhexgal dheer iyo ku-tiirsanaanta faylal badan. Isha la keenay kama warbixiso natiijooyinka soo saarista wax soo saarka, waafaqid browserka, gelitaanka, amniga, ilaalinta, daahitaanka ama iska caabinta khaladaadka qiimeeyaha. Meelahaas waxay si gaar ah u khuseeyaan haddii codsiyada AI-abuuray ay dadku si toos ah u isticmaalaan ama lagu daro nidaamyada software ee waaweyn. Shaqada daba-galka ahi waa inay caddaysaa in calaamadaha abaal-marintu ay hagaajinayaan natiijooyinka dhabta ah ee isticmaalaha iyo haddii ay soo bandhigaan qaabab cusub oo guuldarro ah marka qiimeeyuhu ku meeleeyo qaddarinta muddada koodka khaldan.

Tilmaamaha la xidhiidha & su'aalaha

Moodooyinka AI ayaa la sharaxayTababarka AIWakiilada AITijaabi waxaad taqaan - isku day kedis AI oo bilaash ahKa raadi erey AI qaamuuskeenaRaac qaabka AI raadraaca sii deynta
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