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    <abstract>Recent research has explored the capacity of Large Language Models (LLMs) to perform pragmatic reasoning and interpret complex pragmatic phenomena. However, such phenomena are inherently ambiguous, and even human evaluations are highly variable. Many existing studies directly compare human and model responses while assuming a single “correct” interpretation, thereby overlooking the natural variability that characterizes human pragmatic understanding. This raises two key issues: (1) the need for novel evaluation methods that account for interpretive variability and allow for meaningful comparison between humans and models, and (2) the potential limitations of current linguistic theories in capturing the richness of human pragmatic behavior. We propose that LLMs can serve not only as benchmarks for human-model alignment, but also as tools for investigating the nature of pragmatic phenomena and their relationship to linguistic theory. To this end, we developed a handcrafted dataset encompassing eight types of conversational implicatures. Our study addresses three main research questions: (1) Do LLMs process conversational implicatures differently from humans? (2) If so, how do these differences manifest? (3) What do these findings reveal about the cognitive capacities of LLMs and the explanatory adequacy of pragmatic theory?</abstract>
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%0 Conference Proceedings
%T Conversational Implicatures through the Lens of LLMs
%A Lombardi, Agnese
%A Lenci, Alessandro
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F lombardi-lenci-2026-conversational
%X Recent research has explored the capacity of Large Language Models (LLMs) to perform pragmatic reasoning and interpret complex pragmatic phenomena. However, such phenomena are inherently ambiguous, and even human evaluations are highly variable. Many existing studies directly compare human and model responses while assuming a single “correct” interpretation, thereby overlooking the natural variability that characterizes human pragmatic understanding. This raises two key issues: (1) the need for novel evaluation methods that account for interpretive variability and allow for meaningful comparison between humans and models, and (2) the potential limitations of current linguistic theories in capturing the richness of human pragmatic behavior. We propose that LLMs can serve not only as benchmarks for human-model alignment, but also as tools for investigating the nature of pragmatic phenomena and their relationship to linguistic theory. To this end, we developed a handcrafted dataset encompassing eight types of conversational implicatures. Our study addresses three main research questions: (1) Do LLMs process conversational implicatures differently from humans? (2) If so, how do these differences manifest? (3) What do these findings reveal about the cognitive capacities of LLMs and the explanatory adequacy of pragmatic theory?
%R 10.63317/5dqc2g73d3do
%U https://aclanthology.org/2026.lrec-1.389/
%U https://doi.org/10.63317/5dqc2g73d3do
%P 4955-4966

Markdown (Informal)

[Conversational Implicatures through the Lens of LLMs](https://aclanthology.org/2026.lrec-1.389/) (Lombardi & Lenci, LREC 2026)

• Conversational Implicatures through the Lens of LLMs (Lombardi & Lenci, LREC 2026)

ACL

• Agnese Lombardi and Alessandro Lenci. 2026. Conversational Implicatures through the Lens of LLMs. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 4955–4966, Palma de Mallorca, Spain. ELRA Language Resource Association.