• Exploring undergraduates’ attitudes towards ChatGPT: is AI resistance constraining the acceptance of chatbot technology?

  Sánchez Reina, Jesús Roberto; Theophilou, Emily; Hernández Leo, Davinia; Ognibene, Dimitri (Springer, 2024)

  The advent of Artificial Intelligence (AI) has revolutionized multiple sectors including education. The popularization of tools such as ChatGPT has sparked the debate concerning the impact of AI on traditional education ...
• Generative AI chatbot in PyramidApp: students’ behaviors and design principles

  Gutiérrez-Ferré, Aldric; Hernández Leo, Davinia; Sánchez Reina, Jesús Roberto (Springer, 2024)

  Generative Artificial Intelligence (GenAI) offers new opportunities to implement useful features within Computer Supported Collaborative Learning (CSCL) environments. Despite these growing prospects, there is still limited ...
• IA, contenido visual y periodismo: fundamentos para un debate

  Freixa Font, Pere; Redondo-Arolas, Mar (Asociación Española de Investigación de la Comunicación (AE-IC), 2024)

  La irrupción de la inteligencia artificial (IA) en los medios de comunicación ha provocado un amplio debate académico sobre su potencial transformador. Sin embargo, resulta sorprendente que el fotoperiodismo no se haya ...
• IA y fotoperiodismo: un escenario por definir

  Freixa Font, Pere; Redondo-Arolas, Mar (2023)

  La irrupción de la inteligencia artificial en los medios de comunicación está generando un intenso debate en torno a sus capacidades y repercusiones. Se percibe como una posibilidad o una amenaza según se valore su ...
• SemEval-2016 task 5: aspect based sentiment analysis

  Pontiki, Maria; Galanis, Dimitris; Papageorgiou, Haris; Androutsopoulos, Ion; Manandhar, Suresh; Al-Smadi, Mohammad; Al-Ayyoub, Mahmoud; Zhao, Yanyan; Qin, Bing; De Clercq, Orphée; Hoste, Véronique; Apidianaki, Marianna; Tannier, Xavier; Loukachevitch, Natalia; Kotelnikov, Evgeniy; Bel, Nuria; Bel Rafecas, Núria; Jiménez-Zafra, Salud María; Eryiğit, Gülşen (ACL (Association for Computational Linguistics), 2016)

  This paper describes the SemEval 2016 shared task on Aspect Based Sentiment Analysis (ABSA), a continuation of the respective tasks of 2014 and 2015. In its third year, the task provided 19 training and 20 testing datasets ...
• MemoryPrompt: a light wrapper to improve context tracking in pre-trained language models

  Carraz Rakotonirina, Nathanaël; Baroni, Marco (ELRA (European Language Resources Association), 2024)

  Transformer-based language models (LMs) track contextual information through large, hard-coded input windows. We introduce MemoryPrompt, a leaner approach in which the LM is complemented by a small auxiliary recurrent ...
• Rhetorically-based scalar-additivity: the view from Italian addirittura

  Pistoia-Reda, Salvatore; McNally, Louise, 1965- (Cornell University. Department of Linguistics, 2022)

  Even-like particles have widely been analyzed as inducing scalar and additive presuppositions (cf. Horn 1969; Karttunen & Peters 1979; Rooth 1992; Gast & van der Auwera 2011). However, the additivity of even has been ...
• Reference bias in monolingual machine translation evaluation

  Fomicheva, Marina; Specia, Lucia (ACL (Association for Computational Linguistics), 2016)

  In the translation industry, human translations are assessed by comparison with the source texts. In the Machine Translation (MT) research community, however, it is a common practice to perform quality assessment using a ...
• F-to-c-structure mapping: accounting for inflectional morphology and periphrasis

  Alsina i Keith, Àlex (CSLI Publications, 2023)

  The treatment of inflectional periphrasis is problematic in LFG, apparently because of the lexicalist nature of the framework. A close inspection of what is usually understood by lexicalism reveals two distinct, but ...
• Partitivity in romance and the syntax-morphology connection

  Alsina i Keith, Àlex (CSLI Publications, 2022)

  This paper claims that the relationship between morphology and syntax is multidirectional. It argues against the generally accepted position in LFG that word formation feeds the syntax and that syntax cannot feed word ...
• Unnatural language processing: how do language models handle machine-generated prompts?

  Kervadec, Corentin; Franzon, Francesca; Baroni, Marco (ACL (Association for Computational Linguistics), 2023)

  Language model prompt optimization research has shown that semantically and grammatically well-formed manually crafted prompts are routinely outperformed by automatically generated token sequences with no apparent meaning ...
• Bridging information-theoretic and geometric compression in language models

  Cheng, Emily; Kervadec, Corentin; Baroni, Marco (ACL (Association for Computational Linguistics), 2023)

  For a language model (LM) to faithfully model human language, it must compress vast, potentially infinite information into relatively few dimensions. We propose analyzing compression in (pre-trained) LMs from two points ...
• Referential communication in heterogeneous communities of pre-trained visual deep networks

  Mahaut, Matéo; Franzon, Francesca; Dessì, Roberto; Baroni, Marco (International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2023-07-31)

  As large pre-trained image-processing neural networks are being embedded in autonomous agents such as self-driving cars or robots, the question arises of how such systems can communicate with each other about the ...
• Asking between the lines: elicitation of evoked questions in text

  Westera, Matthijs; Rohde, Hannah (Institute for Logic, Language and Computation (ILLC), 2019)

  We introduce a novel, scalable method aimed at annotating potential and actual Questions Under Discussion (QUDs) in naturalistic discourse. It consists of asking naive participants first what questions a certain portion ...
• Run Like a Girl! Sport-Related Gender Bias in Language and Vision

  Harrison, Sophie; Gualdoni, Eleonora; Boleda, Gemma (ACL (Association for Computational Linguistics), 2023)

  Gender bias in Language and Vision datasets and models has the potential to perpetuate harmful stereotypes and discrimination. We analyze gender bias in two Language and Vision datasets. Consistent with prior work, ...
• Neutralizing the effect of translation shifts on automatic machine translation evaluation

  Fomicheva, Marina; Bel Rafecas, Núria; da Cunha Fanego, Iria (Springer, 2015)

  State-of-the-art automatic Machine Translation [MT] evaluation is based on the idea that the closer MT output is to Human Translation [HT], the higher its quality. Thus, automatic evaluation is typically approached by ...
• Quantifying informativeness of names in visual space

  Gualdoni, Eleonora; Kemp, Charles; Xu, Yang; Boleda, Gemma (Cognitive Science Society, 2023)

  The human lexicon expresses a wide array of concepts with a limited set of words. Previous work has suggested that semantic categories are structured compactly to enable informative communication. Informativeness is typically ...
• Can discrete information extraction prompts generalize across language models?

  Rakotonirina, Nathanael Carraz; Dessì, Roberto; Petroni, Fabio; Riedel, Sebastian; Baroni, Marco (International Conference on Learning Representations (ICLR), 2023)

  We study whether automatically-induced prompts that effectively extract information from a language model can also be used, out-of-the-box, to probe other language models for the same information. After confirming that ...
• Cross-domain image captioning with discriminative finetuning

  Dessì, Roberto; Bevilacqua, Michele; Gualdoni, Eleonora; Rakotonirina, Nathanael Carraz; Franzon, Francesca; Baroni, Marco (Institute of Electrical and Electronics Engineers (IEEE), 2023)

  Neural captioners are typically trained to mimic humangenerated references without optimizing for any specific communication goal, leading to problems such as the generation of vague captions. In this paper, we show ...
• No ordered arguments needed for nouns

  Grimm, Scott; McNally, Louise, 1965- (Institute for Logic, Language and Computation (ILLC), 2013)

  Syntacticians have widely assumed since [11] that there is a fundamental difference between so-called argument structure nominals (AS-nominals, also called Complex Event Nominals), e.g. destruction, and non-AS-nominals, ...

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