The authors isolate the predictive value of token-level certainty by comparing certainty scores against correctness labels on identical generated responses, across multiple LLMs and reasoning tasks.
Token-level certainty predicts LLM question difficulty better than response correctness
Zhou et al. show that the signal's value depends on prediction target and token position, and exploit this to cut test-time token cost by 82.4%.
Chinese Tech
Yunfan Zhou · Ye Zhu · Zhihai Wang · Jianguo Yao · Haibing Guan · Xijun Li
Shanghai Jiao Tong University · Alibaba Group
Research Digest··3 min read
The authors systematically evaluate whether token-level certainty scores from LLMs predict correctness, distinguishing between identifying questions a model will likely answer correctly and distinguishing correct from incorrect responses to the same question.
Why this paper
From Alibaba Group and Shanghai Jiao Tong University
In one line
Token certainty predicts question difficulty better than response correctness, and temporally aligned certainty cuts generation cost while slightly improving accuracy.
What we could check
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