Token Probability Beats Verbalized Condence for Error Detection in Small Open-Weight Language Models: A Medical and Psychiatric Benchmark Study

Kunal Dhanda

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DOI: 10.21203/rs.3.rs-11018466/v1
Published: 2026-09-15
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Publisher: Springer Science and Business Media LLC
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Cite this work

BibTeX

@article{allodium:10.21203/rs.3.rs-11018466/v1,
  title = {Token Probability Beats Verbalized Condence for Error Detection in Small Open-Weight Language Models: A Medical and Psychiatric Benchmark Study},
  author = {Kunal Dhanda},
  year = {2026},
  doi = {10.21203/rs.3.rs-11018466/v1},
  url = {https://doi.org/10.21203/rs.3.rs-11018466/v1}
}

RIS

TY  - JOUR
TI  - Token Probability Beats Verbalized Condence for Error Detection in Small Open-Weight Language Models: A Medical and Psychiatric Benchmark Study
AU  - Kunal Dhanda
PY  - 2026
DO  - 10.21203/rs.3.rs-11018466/v1
UR  - https://doi.org/10.21203/rs.3.rs-11018466/v1
ER  -

APA

Dhanda, K. (2026). Token Probability Beats Verbalized Condence for Error Detection in Small Open-Weight Language Models: A Medical and Psychiatric Benchmark Study. https://doi.org/10.21203/rs.3.rs-11018466/v1

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crossref · retrieved 2026-09-26T09:46:19.077Z