Haakkim/Haakkim-1.0v
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Haakkim
حَكِّم
An open arena-style human preference evaluation platform for Arabic large language models, covering 11 dialect varieties and ranked by a statistically rigorous Bradley–Terry model.
How It Works
Evaluation Modes
Three ways to compare Arabic LLMs — only Ranked Arena feeds the official leaderboard.
Ranked Arena
Random model pairing, single-turn MSA, matched system instruction. The only mode that feeds the official Bradley–Terry leaderboard.
✓ BT LeaderboardSide-by-Side
User-selected model pair, any dialect. Useful for targeted comparisons — excluded from ranked scoring to prevent selection bias.
Win-rate only10 Questions
Fixed Arabic prompt pool, any dialect. Provides consistent benchmarking within a curated question set.
Win-rate onlyOpen Data
Battle Dataset
First public release of Haakkim battle data — fully open, PII-scrubbed, ready to use.
Haakkim / Haakkim-1.0v
Battle records covering all 11 dialect varieties and all 3 evaluation modes. Includes full conversation transcripts, sampling weights, and category annotations.
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Team
College of Computing, Umm Al-Qura University — Mecca, Saudi Arabia
Research
Citation
If you use Haakkim or this dataset in your research, please cite:
@misc{mars2026haakkim,
title = {Haakkim: An Arena-Style Human Preference Evaluation Platform for Arabic {LLMs}},
author = {Mars, Mourad and Barmandah, Hassan and Alassaf, Abdulrhman},
year = {2026},
howpublished = {\url{https://huggingface.co/datasets/Haakkim/Haakkim-1.0v}},
note = {College of Computing, Umm Al-Qura University, Mecca, Saudi Arabia}
}
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