Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Plepi, Joan"'
Autor:
Nie, Shangrui, Fromm, Michael, Welch, Charles, Görge, Rebekka, Karimi, Akbar, Plepi, Joan, Mowmita, Nazia Afsan, Flores-Herr, Nicolas, Ali, Mehdi, Flek, Lucie
While preliminary findings indicate that multilingual LLMs exhibit reduced bias compared to monolingual ones, a comprehensive understanding of the effect of multilingual training on bias mitigation, is lacking. This study addresses this gap by system
Externí odkaz:
http://arxiv.org/abs/2407.05740
Autor:
Sarumi, Olufunke O., Neuendorf, Béla, Plepi, Joan, Flek, Lucie, Schlötterer, Jörg, Welch, Charles
Recent trends in natural language processing research and annotation tasks affirm a paradigm shift from the traditional reliance on a single ground truth to a focus on individual perspectives, particularly in subjective tasks. In scenarios where anno
Externí odkaz:
http://arxiv.org/abs/2404.02340
Instead of using a single ground truth for language processing tasks, several recent studies have examined how to represent and predict the labels of the set of annotators. However, often little or no information about annotators is known, or the set
Externí odkaz:
http://arxiv.org/abs/2210.14531
Studies on interpersonal conflict have a long history and contain many suggestions for conflict typology. We use this as the basis of a novel annotation scheme and release a new dataset of situations and conflict aspect annotations. We then build a c
Externí odkaz:
http://arxiv.org/abs/2208.08758
Autor:
Sakketou, Flora, Plepi, Joan, Cervero, Riccardo, Geiss, Henri-Jacques, Rosso, Paolo, Flek, Lucie
Proactively identifying misinformation spreaders is an important step towards mitigating the impact of fake news on our society. In this paper, we introduce a new contemporary Reddit dataset for fake news spreader analysis, called FACTOID, monitoring
Externí odkaz:
http://arxiv.org/abs/2205.06181
Medical diagnosis is the process of making a prediction of the disease a patient is likely to have, given a set of symptoms and observations. This requires extensive expert knowledge, in particular when covering a large variety of diseases. Such know
Externí odkaz:
http://arxiv.org/abs/2204.13329
Autor:
Plepi, Joan, Flek, Lucie
Existing sarcasm detection systems focus on exploiting linguistic markers, context, or user-level priors. However, social studies suggest that the relationship between the author and the audience can be equally relevant for the sarcasm usage and inte
Externí odkaz:
http://arxiv.org/abs/2110.04001
Autor:
Kacupaj, Endri, Plepi, Joan, Singh, Kuldeep, Thakkar, Harsh, Lehmann, Jens, Maleshkova, Maria
This paper addresses the task of (complex) conversational question answering over a knowledge graph. For this task, we propose LASAGNE (muLti-task semAntic parSing with trAnsformer and Graph atteNtion nEtworks). It is the first approach, which employ
Externí odkaz:
http://arxiv.org/abs/2104.01569
Neural semantic parsing approaches have been widely used for Question Answering (QA) systems over knowledge graphs. Such methods provide the flexibility to handle QA datasets with complex queries and a large number of entities. In this work, we propo
Externí odkaz:
http://arxiv.org/abs/2103.07766