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Self-Consistency Decoding
Self-consistency samples multiple reasoning paths and aggregates their extracted answers, often by majority vote.
Teerera kugwaro iriAI-yakarondedzerwa · ~2 min
Pa peji ino2 min verenga
Pfupiso
It improved results on several studied benchmarks, but accuracy gains depend on the task and samples can share correlated errors; the method also adds inference cost.
Kudzika Kwakadzika
A model can produce different reasoning paths for the same prompt. Greedy decoding follows one most-likely path, while self-consistency samples several paths, extracts an answer from each, and selects the most frequent answer. The original study reported improvements on several arithmetic and commonsense benchmarks under its tested models, prompts, and sampling budgets. On suitable tasks, correct paths may converge more consistently than incorrect paths, but this is not guaranteed: paths come from the same model and errors may be correlated. Answer extraction and normalization also matter because equivalent answers can have different surface forms. The method increases inference work because it generates multiple paths. Treat the vote as an aggregation heuristic and use external checks when correctness matters.
Kuitwa muNyika yeChokwadi
Kuwedzera huchokwadi pagiredhi-chikoro math emazwi matambudziko (GSM8K) nekuenzanisa nzira dzakawanda dzemhinduro uye kuvhota panhamba yekupedzisira.
Kuvandudza kuvimbika kwemubvunzo we-multi-nhanho commonsense uchipindura apo cheni imwe chete inogona kutsvedza pane imwe fungidziro.
Kuwedzera kusavimbika mumhinduro dzechizvarwa chekodhi nekutarisa kuti ndezvipi zvinobuda zvinowanzoitika pamasamples.
Kusimbisa mabasa ekufananidzira kana ane musoro apo zvirevo zvakasiyana-siyana zvinofanira kusangana pamhedziso imwe yakarurama.
Ramangwana reKuzvimiririra Decoding
Kuzvimiririra muenzaniso wekutanga wekuyeresa-nguva kuyera, uye vazukuru vayo ikozvino masimba ekufunga mamodheru anoshandisa yakawedzera compute kufunga zvakanyanya. Nhungamiro dzeramangwana dzinosanganisira kuyera mavhoti nemunhu akadzidza kana zvibodzwa zvekuvimbika pane kuverenga zvakaenzana, achisarudza kuti masampuli mangani ekudhirowa zvichienderana nekuoma kwemibvunzo, uye kubatanidza kuvhota nemaitiro ekutsvaga seMuti Wepfungwa. Tarisira kuti irambe yakachipa, yekudzidzira-yemahara yekutanga iyo chero system inogona kuisa pairi kana iko kurongeka kwakakosha kupfuura latency.
Kuzvishandisa
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Matanho anotevera
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Take the Self-Consistency Decoding quiz
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Mibvunzo inowanzo bvunzwa
What is Self-Consistency Decoding?
Self-consistency samples multiple reasoning paths and aggregates their extracted answers, often by majority vote. It improved results on several studied benchmarks, but accuracy gains depend on the task and samples can share correlated errors; the method also adds inference cost.
How does self-consistency decoding pick a final answer from a language model?
Kuzvimiririra sampuli dzakawanda dzakasiyana-siyana dzekufunga uye inosarudza mhinduro yekupedzisira inobvumirana nemaketani mazhinji.
Under what condition can self-consistency improve answer accuracy?
Self-consistency can help on tested tasks when correct samples converge and mistakes vary; correlated errors can still make a wrong majority.
Ndeipi nzira yekudhirodha inotsiva yega-inotsiva?
Panzvimbo pekuita nemakaro kune imwe nzira-ingangodaro, yekuzvimiririra masampula uye akaunganidzwa munzira dzakawanda.
Ndeipi chikamu checheni yega yega yemuenzaniso chinonyatso shandiswa muvhoti yekupedzisira?
Kufunga kwepakati kunoraswa; mhinduro dzekupedzisira chete dzinounganidzwa nevhoti yeruzhinji.
What is the main cost of increasing the number of self-consistency samples?
The paper reports gains in its evaluated tasks, but more samples do not guarantee higher accuracy because errors can be correlated.
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