Which Models Perform Better in Inheritance Reasoning?
This paper presents the participation of team PSL in the QIAS 2026 Shared Task on Arabic Islamic inheritance reasoning. The task evaluates large language models on solving inheritance cases requiring legal interpretation, multi-step reasoning, and precise numerical computation. Results show commercial models like Gemini 2.5 Flash outperform open-source models in identifying heirs, applying exclusion rules, and maintaining consistency, while open-source models exhibit instability.
[2606.13751] Which Models Perform Better in Inheritance Reasoning?
[Submitted on 11 Jun 2026]
Title:Which Models Perform Better in Inheritance Reasoning?
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Abstract:This paper presents the participation of team PSL in the QIAS 2026 Shared Task on Arabic Islamic inheritance reasoning. The task evaluates the ability of large language models to solve inheritance cases that require legal interpretation, multi-step reasoning, and precise numerical computation. We compare \textit{commercial} and \textit{open-source} models under a unified prompting strategy to assess their effectiveness in structured legal reasoning with minimal task-specific adaptation. \\ Our results show a clear gap in reliability between the two model families. Commercial models demonstrate stronger performance in identifying eligible heirs, applying exclusion rules, and maintaining consistency across reasoning steps. In contrast, open-source models exhibit greater instability, particularly in cases involving dependent legal decisions and fractional share adjustments. The best performance is achieved by \textit{Gemini 2.5 Flash}, with an MRE of $0.989$.
Subjects:
Computation and Language (cs.CL)
Cite as: arXiv:2606.13751 [cs.CL]
(or arXiv:2606.13751v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2606.13751
arXiv-issued DOI via DataCite
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From: Mouhoub Amine [view email] [v1] Thu, 11 Jun 2026 15:23:32 UTC (26 KB)
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