activity
20182022
most citedEarly Risk Detection of Pathological Gambling, Self-Harm and Depression Using BERT

18 citations · 27 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CL2022

Life is not Always Depressing: Exploring the Happy Moments of People Diagnosed with Depression

Ana-Maria Bucur, Adrian Cosma, Liviu P. Dinu

In this work, we explore the relationship between depression and manifestations of happiness in social media. While the majority of works surrounding depression focus on symptoms,…

cs.CL20227 cited

BLUE at Memotion 2.0 2022: You have my Image, my Text and my Transformer

Ana-Maria Bucur, Adrian Cosma, Ioan-Bogdan Iordache

Memes are prevalent on the internet and continue to grow and evolve alongside our culture. An automatic understanding of memes propagating on the internet can shed light on the gen…

cs.CV2021

From Face to Gait: Weakly-Supervised Learning of Gender Information from Walking Patterns

Andy Catruna, Adrian Cosma, Ion Emilian Radoi

Obtaining demographics information from video is valuable for a range of real-world applications. While approaches that leverage facial features for gender inference are very succe…

cs.CL20211 cited

Sequence-to-Sequence Lexical Normalization with Multilingual Transformers

Ana-Maria Bucur, Adrian Cosma, Liviu P. Dinu

Current benchmark tasks for natural language processing contain text that is qualitatively different from the text used in informal day to day digital communication. This discrepan…

cs.CL202118 cited

Early Risk Detection of Pathological Gambling, Self-Harm and Depression Using BERT

Ana-Maria Bucur, Adrian Cosma, Liviu P. Dinu

Early risk detection of mental illnesses has a massive positive impact upon the well-being of people. The eRisk workshop has been at the forefront of enabling interdisciplinary res…

cs.CV2020

Black-Box Ripper: Copying black-box models using generative evolutionary algorithms

Antonio Barbalau, Adrian Cosma, Radu Tudor Ionescu +1

We study the task of replicating the functionality of black-box neural models, for which we only know the output class probabilities provided for a set of input images. We assume b…