HakemBench: A Turkish Benchmark of Typed Decisions
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Abstract (arXiv)
HakemBench is a Turkish benchmark of typed decisions, in which the model under test reads a text, a question and a fixed set of options and returns a probability for every option. Version 1.0 is released fully open under CC BY 4.0, with 2,346 items and 4,275 choice, yes/no and score questions in seven tracks (fact-check triage, education, guardrails, legal routing, moderation, spam and phishing, and customer support). One harness scores decision quality (macro F1), calibration (from the normalised Brier score) and selective automation (from the normalised area under the generalised risk-coverage curve), combines them by a geometric mean and reports intervals from 2,000 bootstrap draws; probes for option order, paraphrase, English translation and substituted names are reported alongside. Most gold labels come from blind passes of one AI model family compared with the votes of a panel of large language models from other model families; they are not human-verified. On a board of 16 rows the leader scores a composite of 0.888 and the lab's own model is 7th at 0.660. Its numbers are not blind. Earlier runs' test results shaped its training data, so its guardrail, moderation and customer support numbers are flagged; with every model scored on the other four tracks only, its composite is 0.678, 6th of 16.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 18 of its 32 references that are in the map. First posted on arXiv 1 Oct 2026.
Builds on
18 of 32 references.
References · 18
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- 2025Cetvel: A Unified Benchmark for Evaluating Language Understanding, Generation and Cultural Capacity of LLMs for Turkishcited by 8
6 more
- 2026TurkBench: A Benchmark for Evaluating Turkish Large Language Modelscited by 5
- 2024Turkronicles: Diachronic Resources for the Fast Evolving Turkish Languagecited by 4
- 2025Introducing TrGLUE and SentiTurca: A Comprehensive Benchmark for Turkish General Language Understanding and Sentiment Analysiscited by 3
- 2026ABCD: All Biases Come Disguisedcited by 3
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Citing papers per year: 2026: 1.
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