This article introduces the concept of multimodal oxymorons. Multimodal oxymorons extend the traditional oxymoron theory by constructing and communicating meaning through the interplay of multiple modalities (such as visual and textual) rather than relying solely on language. We argue that multimodal oxymorons are central mechanisms of meaning-making in contemporary communication, as evidenced by the use of memes as an example. While textual oxymorons have long been the subject of analysis in order to ascertain their role in shaping thought and meaning, multimodal oxymorons demonstrate how human cognitive process transcends linguistic boundaries, integrating different modalities (e.g., visual) in order to convey complex ideas. To encourage further study, we present a curated multilingual dataset of Multimodal OXYmoron (MOXY), which can be used as a foundation for further analysis and experimentation. Furthermore, we propose a methodical approach for the identification of multimodal oxymorons along with a pipeline for automated generation. Through illustrative examples and a detailed methodology, this work establishes a comprehensive framework for understanding, identifying, and generating multimodal oxymorons, paving the way for advancements in computational linguistics, artificial intelligence, and figurative language studies.

In this paper, we examine the competition between pairs of adjectives in Italian that are antonyms of the same term: one is a “morphological antonym” formed by negative prefixation, the other is a “lexical antonym” with no morphological relationship with the term in question. We consider pairs of adjectives that are reported as antonyms in lexicographic resources and extract the nouns that can be modified by both adjectives from a large corpus. We select a set of 8 nouns for each pair that present higher, lower, and comparable frequencies combined with each antonym respectively and then we perform two experiments with a LLM. Firstly, we perform experiments for masked-token prediction of the adjective, to study the correlation between prediction accuracy and the frequency of the noun-antonym pair. Secondly, we perform a polarity-flip experiment with a multilingual LLM, asking to change the adjective into its positive counterpart, and study the cases where the antonym is changed to the morphological antonym’s lexical base, under the hypothesis that a flip to the lexical base indicates a narrower set of senses of the antonymic counterpart.

The paper presents a pilot exploration of the construction, management and analysis of a multimodal corpus. Through athree-layer annotation that provides orthographic, prosodic, and gestural transcriptions, the gest-IT resource allows oneto investigate the variation of gesture-making patterns in conversations between sighted people and people with visualimpairment. After discussing the transcription methods and technical procedures employed in our study, we will propose aunified CoNLL-U corpus and indicate our future steps.

This paper contains a preliminary corpus study of oxymorons, a figure of speech so far under-investigated in NLP-oriented research. The study resulted in a list of 376 oxymorons, identified by extracting a set of antonymous pairs (under various configurations) from corpora of written Italian and by manually checking the results. A complementary method is also envisaged for discovering contextual oxymorons, which are highly relevant for the detection of humor, irony and sarcasm.