90 citations · 205 across the 21 of their papers we have counts for
23 papers
The Scenario Refiner: Grounding subjects in images at the morphological level
Claudia Tagliaferri, Sofia Axioti, Albert Gatt +1
Derivationally related words, such as "runner" and "running", exhibit semantic differences which also elicit different visual scenarios. In this paper, we ask whether Vision and La…
Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP
Anya Belz, Craig Thomson, Ehud Reiter +39
We report our efforts in identifying a set of previous human evaluations in NLP that would be suitable for a coordinated study examining what makes human evaluations in NLP more/le…
On the interaction of automatic evaluation and task framing in headline style transfer
Lorenzo De Mattei, Michele Cafagna, Huiyuan Lai +3
An ongoing debate in the NLG community concerns the best way to evaluate systems, with human evaluation often being considered the most reliable method, compared to corpus-based me…
Seeing past words: Testing the cross-modal capabilities of pretrained V&L models on counting tasks
Letitia Parcalabescu, Albert Gatt, Anette Frank +1
We investigate the reasoning ability of pretrained vision and language (V&L) models in two tasks that require multimodal integration: (1) discriminating a correct image-sentence pa…
Datasets and Models for Authorship Attribution on Italian Personal Writings
Gaetana Ruggiero, Albert Gatt, Malvina Nissim
Existing research on Authorship Attribution (AA) focuses on texts for which a lot of data is available (e.g novels), mainly in English. We approach AA via Authorship Verification o…
Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender Bias
Marion Bartl, Malvina Nissim, Albert Gatt
Contextualized word embeddings have been replacing standard embeddings as the representational knowledge source of choice in NLP systems. Since a variety of biases have previously…