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Reflexion is a research framework in which language agents use task feedback to write textual reflections for later attempts.
Déglul tegtal biiIA-nettali · ~1 min
It changes context, not model weights.
The Reflexion paper describes an Actor that attempts a task, an Evaluator that scores the result, and a Self-Reflection model that turns feedback into language stored in episodic memory. The next attempt can use that reflection as context; the framework does not update model weights. The paper reports improvements on selected tasks, including a HumanEval result for its particular setup. Benchmark results should not be generalized to every agent or deployment. In the Reflexion paper’s reported coding experiment, the framework achieved 91% pass@1 on HumanEval, compared with 80% for the GPT-4 baseline described in that paper. These are results for the paper’s particular setup and benchmark, not a general performance guarantee.
An agent receives unit-test feedback, writes a reflection, and retries a coding task.
A researcher compares Reflexion’s benchmark setup with its stated baseline.
An evaluator supplies task-specific feedback that the agent can inspect.
A developer stops iteration when a defined success condition is met.
Self-correction methods remain dependent on evaluation quality, task design, and iteration cost. Avoid claims of general improvement without testing; reflections can be mistaken or lead to loops.
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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.
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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
Reflexion is a research framework in which language agents use task feedback to write textual reflections for later attempts. It changes context, not model weights.
Yenn saa yi dañuy woowe reflexion 'jàngat buy dooleel kàddu' ndax njàngale yi dañu leen denc ci memër bi ni mbindu làkk wiñ nàmp, duñu ko enkode ci parametru model bi.
Evaluateur bi (test unité, check match exact, wala àttekat LLM) mooy defar siñaal biy wane ni jéego Self-Reflection dafay soppiku nekk njàngale buñ bind.
Sudee jàngat bi wóorul dara, ndawu liggéey bi mën na bind ay xalaat yu wóolu boppam yu sukkandiko ci feedback bu baaxul, di yóbbu jéem yi ci kanam ci yoon wu jaarul yoon.
The paper reports 91% pass@1 on HumanEval for its Reflexion coding setup; the result is specific to that evaluation.
Ku amul sàrtu taxawal bu baax, ab ndawu liggéey mën na wéy di xoolaat tontu yu jaar yoon, yàq ordinatër bi, yenn saa muy yàq njariñ li.
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Tann nañu yeneen njiit ngir topic bii
Ci bi mu melGis bi ci topp
Xalaatal sa bopp ci boucles agent
Xarala