Xiga xigaHagaha xiga
Wakiilada-fuliyaha Qorsheeyaha
Codsiyada
HAGAHA Codsiyada
ReAct waa qaab kicinta luuqada-qaabka kaas oo ka dhexeeya raadraaca sababaynta ficillada iyo indho-indheynta aaladaha dibadda ama deegaanka.
Dhageyso hagahanAI-waa laga sheekeeyay · ~1 min
The original paper evaluates it on knowledge-intensive question answering and interactive decision-making tasks.
The ReAct paper prompts language models to interleave reasoning traces and task-specific actions, using observations from an external environment to update plans. It evaluates HotpotQA and FEVER with a Wikipedia API and interactive decision benchmarks including ALFWorld and WebShop. The authors report a 34-point absolute success-rate improvement on ALFWorld and 10 points on WebShop over the baselines used in their experiments. These findings are specific to the tested tasks and prompts.
Representing a trajectory as Thought, Action, Observation and a final answer.
Using the paper’s Wikipedia API to retrieve evidence for HotpotQA and FEVER questions.
Updating a plan after an environment returns an observation.
Comparing the original paper’s ReAct results with reasoning-only and acting-only baselines in its tested tasks.
Evaluate ReAct-style loops on the specific environment, tool reliability and task distribution. Include access limits, error handling and stopping conditions; the paper’s benchmark results do not guarantee safety or accuracy in unrelated deployments.
Warqad bilaash ah
Saddex sheeko oo la xaqiijiyay oo AI ah maalin kasta oo shaqo ah, oo lagu qoray Ingiriis fudud. Bilaash had iyo jeer, aan xayaysiis lahayn.
Hal iimayl maalin kasta oo shaqo ah. Ka bax hal gujin. Marna ma iibinno ama ma wadaagno ciwaankaaga.
Is tijaabi
Fikrad degdeg ah oo ku saabsan jawaab kasta, iyo shahaado la wadaajin karo oo leh aqoonsi la xaqiijin karo markaad ka gudubto koorso.
Taageer waxbarashada AI bilaashka ah. AI Understanding waa 501(c)(3) aan faa'iido doon ahayn — xayaysiis la'aan, albaab lacag ah ma jiro, had iyo jeer. Samee deeq
ReAct is a language-model prompting pattern that interleaves reasoning traces with actions and observations from an external tool or environment. The original paper evaluates it on knowledge-intensive question answering and interactive decision-making tasks.
ReAct waxay u taagan tahay Sababta iyo Ku-dhaqanka; Waxay ka dhexaysaa fikradda silsiladda-fikirka leh ficillo la taaban karo sida wicitaannada aaladaha.
Wareegga loop ReAct wuxuu ku wareegaa Fikrad (Qorshe), Ficil (qalab wicitaan), iyo Kormeer (natiijada), ku celcelinta ilaa la sameeyo.
Kormeerku waa jawaab celinta uu nidaamku soo celiyo ka dib markii uu socodsiiyo qaabka uu doortay Ficilka, kaas oo moodeelku sabab u yahay.
Isaga oo ku dhex milmay sababaynta indha-indhaynta dhabta ah ee agabka, qaabku waxa uu hubin karaa xaqiiqooyinka iyo koorsada saxda ah halkii uu jawaabo ka abuuri lahaa.
The original ReAct paper reports an absolute success-rate improvement of 34 points over imitation and reinforcement-learning baselines on ALFWorld, with a separate 10-point result on WebShop; this is scoped to its experiments.
Sii wad waxbarashada
Tilmaamayaal badan ayaa loo doortay mawduucan
Xiga xigaHagaha xiga
Wakiilada-fuliyaha Qorsheeyaha
Codsiyada