Question Selection and Answer Scoring Shape Revision Risk in Recurrent Language Models
Tests how answer scoring changes measurements of early-answer stability in Huginn and Ouro. Shows that choosing which questions to answer early and deciding what counts as an answer change must be evaluated separately; lower revision risk did not establish better accuracy or stopping decisions.
First public: · Added to this list: October 19, 2026
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Question Selection and Answer Scoring Shape Revision Risk in Recurrent Language Models
Ruian Lei, Yazhou Ren, Zenglin Xu
Applied Sciences, 2026, 16(19), article 9857.
DOI: 10.3390/app16199857
Checked 2026-10-19 against the publication record.
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Analysis and evaluation — Measure how well these methods work, investigate what their internal computation does, and identify where they fail. This includes experiments, studies of model internals, and mathematical results.
Recurrent reasoning — Repeat parts of the model or keep intermediate information in memory while working through a problem. Some methods also learn how many passes to run.
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