278 citations · 1.2k across the 40 of their papers we have counts for
50 papers
Stereotypical gender actions can be extracted from Web text
Amaç Herdağdelen, Marco Baroni
We extracted gender-specific actions from text corpora and Twitter, and compared them to stereotypical expectations of people. We used Open Mind Common Sense (OMCS), a commonsense…
Cross-Domain Image Captioning with Discriminative Finetuning
Roberto Dessì, Michele Bevilacqua, Eleonora Gualdoni +3
Neural captioners are typically trained to mimic human-generated references without optimizing for any specific communication goal, leading to problems such as the generation of va…
Can discrete information extraction prompts generalize across language models?
Nathanaël Carraz Rakotonirina, Roberto Dessì, Fabio Petroni +2
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 s…
Referential communication in heterogeneous communities of pre-trained visual deep networks
Matéo Mahaut, Francesca Franzon, Roberto Dessì +1
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 commu…
Communication breakdown: On the low mutual intelligibility between human and neural captioning
Roberto Dessì, Eleonora Gualdoni, Francesca Franzon +2
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 condu…
How BPE Affects Memorization in Transformers
Eugene Kharitonov, Marco Baroni, Dieuwke Hupkes
Training data memorization in NLP can both be beneficial (e.g., closed-book QA) and undesirable (personal data extraction). In any case, successful model training requires a non-tr…