Unverified50% confidenceFactExact time
At each step, the remask sampler prioritizes confirming high-confidence positions based on model predictions and then remasks the remaining positions.
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50%
Confidence
Long-term
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10/2/2026
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Related Claims
UnverifiedUsing a confidence-first strategy during decoding (prioritizing the positions the model is most confident about) typically delivers significantly better generation quality than uniformly revealing a fixed proportion of tokens, because it allows the model to decide on difficult positions after having more context.80% similarUnverifiedIn multi-hop reasoning scenarios, each hop's retrieval should incrementally supplement based on the conclusions of the previous hop, and the decision model can explicitly track the known information set to avoid redundant recall.75% similarUnverifiedReranking is the process of using a fine-ranking model to re-score and re-sort candidate segments after an initial Top-K retrieval, in order to improve the quality of the context fed into the large model.73% similarUnverifiedReAct范式通过强制要求每次工具调用后观察真实环境反馈，将推理链锚定在可验证的现实结果上，抑制错误累积73% similarUnverified分类模型的推理是非自回归的，仅需一次前向传播即可完成所有位置预测，计算效率显著高于生成模型71% similar
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