13 citations · 15 across the 7 of their papers we have counts for
7 papers
Analysing zero-shot temporal relation extraction on clinical notes using temporal consistency
Vasiliki Kougia, Anastasiia Sedova, Andreas Stephan +2
This paper presents the first study for temporal relation extraction in a zero-shot setting focusing on biomedical text. We employ two types of prompts and five LLMs (GPT-3.5, Mixt…
Exploring prompts to elicit memorization in masked language model-based named entity recognition
Yuxi Xia, Anastasiia Sedova, Pedro Henrique Luz de Araujo +3
Training data memorization in language models impacts model capability (generalization) and safety (privacy risk). This paper focuses on analyzing prompts' impact on detecting the…
MemeGraphs: Linking Memes to Knowledge Graphs
Vasiliki Kougia, Simon Fetzel, Thomas Kirchmair +4
Memes are a popular form of communicating trends and ideas in social media and on the internet in general, combining the modalities of images and text. They can express humor and s…
SepLL: Separating Latent Class Labels from Weak Supervision Noise
Andreas Stephan, Vasiliki Kougia, Benjamin Roth
In the weakly supervised learning paradigm, labeling functions automatically assign heuristic, often noisy, labels to data samples. In this work, we provide a method for learning f…
Diagnostic Captioning: A Survey
John Pavlopoulos, Vasiliki Kougia, Ion Androutsopoulos +1
Diagnostic Captioning (DC) concerns the automatic generation of a diagnostic text from a set of medical images of a patient collected during an examination. DC can assist inexperie…
RTEX: A novel methodology for Ranking, Tagging, and Explanatory diagnostic captioning of radiography exams
Vasiliki Kougia, John Pavlopoulos, Panagiotis Papapetrou +1
This paper introduces RTEx, a novel methodology for a) ranking radiography exams based on their probability to contain an abnormality, b) generating abnormality tags for abnormal e…
A Survey on Biomedical Image Captioning
Vasiliki Kougia, John Pavlopoulos, Ion Androutsopoulos
Image captioning applied to biomedical images can assist and accelerate the diagnosis process followed by clinicians. This article is the first survey of biomedical image captionin…