• 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, ...
• Does referent predictability affect the choice of referential form? A computational approach using masked coreference resolution

  Aina, Laura; Liao, Xixian; Boleda, Gemma; Westera, Matthijs (ACL (Association for Computational Linguistics), 2021)

  It is often posited that more predictable parts of a speaker’s meaning tend to be made less explicit, for instance using shorter, less informative words. Studying these dynamics in the domain of referring expressions has ...
• Challenges in including extra-linguistic context in pre-trained language models

  Sorodoc, Ionut-Teodor; Aina, Laura; Boleda, Gemma (ACL (Association for Computational Linguistics), 2022)

  To successfully account for language, computational models need to take into account both the linguistic context (the content of the utterances) and the extra-linguistic context (for instance, the participants in a dialogue). ...
• How universal is metonymy? Results from a large-scale multilingual analysis

  Khishigsuren, Temuulen; Bella, Gábor; Brochhagen, Thomas; Marav, Daariimaa; Giunchiglia, Fausto; Batsuren, Khuyagbaatar (ACL (Association for Computational Linguistics), 2022)
• Introducing QuBERT: a large monolingual corpus and BERT model for Southern Quechua

  Zevallos, Rodolfo; Ortega, John E.; Chen, William; Castro, Richard; Bel Rafecas, Núria; Yoshikawa, Cesar; Ventura, Renzo; Aradiel, Hilario; Melgarejo, Nelsi (ACL (Association for Computational Linguistics), 2022)

  The lack of resources for languages in the Americas has proven to be a problem for the creation of digital systems such as machine translation, search engines, chat bots, and more. The scarceness of digital resources for ...
• Data augmentation for low-resource Quechua ASR improvement

  Zevallos, Rodolfo; Bel Rafecas, Núria; Cámbara Ruiz, Guillermo; Farrús, Mireia; Luque, Jordi (International Speech Communication Association (ISCA), 2022)

  Automatic Speech Recognition (ASR) is a key element in new services that helps users to interact with an automated system. Deep learning methods have made it possible to deploy systems with word error rates below 5% for ...
• Metaphorical measure expressions

  Sutton, Peter R.; Filip, Hana; Snider, Todd; Windhearn, Mia (University of Konstanz, 2021)

  We present an analysis of measure phrases such as heap/ounce of information in which the measure expression receives a non-literal, metaphorical interpretation. We present evidence that these metaphorical measure ...
• Restrictions on copredication: a situation theoretic approach

  Sutton, Peter R. (Cornell University, Linguistic Society of America, 2022)

  This paper proposes a situation theoretic account of polysemy: polysemous nouns denote situations that witness (i.e. contain) multiple entities of different types. For instance, lunch denotes situations that contain an ...
• Communication breakdown: on the low mutual intelligibility between human and neural captioning

  Dessì, Roberto; Gualdoni, Eleonora; Franzon, Francesca; Boleda, Gemma; Baroni, Marco (ACL (Association for Computational Linguistics), 2022)

  We compare the 0-shot performance of a neural caption-based image retriever when given as input either human-produced captions or captions generated by a neural captioner. We conduct this comparison on the recently ...
• Emergent language generalization and acquisition speed are not tied to compositionality

  Kharitonov, Eugene; Baroni, Marco (ACL (Association for Computational Linguistics), 2020)

  Studies of discrete languages emerging when neural agents communicate to solve a joint task often look for evidence of compositional structure. This stems for the expectation that such a structure would allow languages ...
• CNNs found to jump around more skillfully than RNNs: compositional generalization in seq2seq convolutional networks

  Dessi, Roberto; Baroni, Marco (ACL (Association for Computational Linguistics), 2019)

  Lake and Baroni (2018) introduced the SCAN dataset probing the ability of seq2seq models to capture compositional generalizations, such as inferring the meaning of “jump around” 0- shot from the component words. ...
• Obligatory clitic expression, clitic omission, and the morphology-syntax interface

  Alsina i Keith, Àlex (CSLI Publications, 2020)

  In the Romance language Catalan, some verbs and some argument-structure configurations normally require the reflexive clitic; however, in certain constructions, the expected reflexive clitic is optionally missing; and, ...
• Interpretable agent communication from scratch (with a generic visual processor emerging on the side)

  Dessì, Roberto; Kharitonov, Eugene; Baroni, Marco (Neural Information Processing Systems (NeurIPS), 2021)

  As deep networks begin to be deployed as autonomous agents, the issue of how they can communicate with each other becomes important. Here, we train two deep nets from scratch to perform large-scale referent identification ...
• Controlled tasks for model analysis: retrieving discrete information from sequences

  Sorodoc, Ionut-Teodor; Boleda, Gemma; Baroni, Marco (ACL (Association for Computational Linguistics), 2021)

  In recent years, the NLP community has shown increasing interest in analysing how deep learning models work. Given that large models trained on complex tasks are difficult to inspect, some of this work has focused ...
• Accesibilidad en las plataformas de vídeo actuales: Repaso de la oferta de servicios en España

  Arias Badia, Blanca (HispaTAV - Congreso Hispanoamericano de Traducción Audiovisual, 2020-11)

  Infografía presentada en la jornada HispaTAV, en la que se recoge la oferta de servicios de accesibilidad en lengua española y lengua de signos española en las plataformas Netflix, HBO, Disney+, AppleTV, Filmin, PrimeVideo ...

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