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        <title>LOGICAL-COMMONSENSEQA: A Benchmark for Logical Commonsense Reasoning</title>
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        <namePart type="given">Obed</namePart>
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            <namePart type="given">Maria</namePart>
            <namePart type="family">Liakata</namePart>
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            <namePart type="given">Viviane</namePart>
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            <namePart type="given">Jiajun</namePart>
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    <abstract>Commonsense reasoning often involves evaluating multiple plausible interpretations rather than selecting a single atomic answer, yet most benchmarks rely on single-label evaluation, obscuring whether statements are jointly plausible, mutually exclusive, or jointly implausible. We introduce LOGICAL-COMMONSENSEQA, a benchmark that reframes commonsense reasoning as logical composition over pairs of atomic statements using plausibility-level operators (AND, OR and NEITHER/NOR). Evaluating instruction-tuned, reasoning-specialized, and fine-tuned models under zero-shot, few-shot, and chain-of-thought prompting, we find that while models perform reasonably on conjunctive and moderately on disjunctive reasoning, performance degrades sharply on negation-based questions. LOGICAL-COMMONSENSEQA exposes fundamental reasoning limitations and provides a controlled framework for advancing compositional commonsense reasoning.</abstract>
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%0 Conference Proceedings
%T LOGICAL-COMMONSENSEQA: A Benchmark for Logical Commonsense Reasoning
%A Junias, Obed
%A Pacheco, Maria Leonor
%Y Liakata, Maria
%Y Moreira, Viviane P.
%Y Zhang, Jiajun
%Y Jurgens, David
%S Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, United States
%@ 979-8-89176-391-3
%F junias-pacheco-2026-logical
%X Commonsense reasoning often involves evaluating multiple plausible interpretations rather than selecting a single atomic answer, yet most benchmarks rely on single-label evaluation, obscuring whether statements are jointly plausible, mutually exclusive, or jointly implausible. We introduce LOGICAL-COMMONSENSEQA, a benchmark that reframes commonsense reasoning as logical composition over pairs of atomic statements using plausibility-level operators (AND, OR and NEITHER/NOR). Evaluating instruction-tuned, reasoning-specialized, and fine-tuned models under zero-shot, few-shot, and chain-of-thought prompting, we find that while models perform reasonably on conjunctive and moderately on disjunctive reasoning, performance degrades sharply on negation-based questions. LOGICAL-COMMONSENSEQA exposes fundamental reasoning limitations and provides a controlled framework for advancing compositional commonsense reasoning.
%U https://aclanthology.org/2026.acl-short.61/
%P 746-758

Markdown (Informal)

[LOGICAL-COMMONSENSEQA: A Benchmark for Logical Commonsense Reasoning](https://aclanthology.org/2026.acl-short.61/) (Junias & Pacheco, ACL 2026)

• LOGICAL-COMMONSENSEQA: A Benchmark for Logical Commonsense Reasoning (Junias & Pacheco, ACL 2026)

ACL

• Obed Junias and Maria Leonor Pacheco. 2026. LOGICAL-COMMONSENSEQA: A Benchmark for Logical Commonsense Reasoning. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 746–758, San Diego, California, United States. Association for Computational Linguistics.