18 citations · 40 across the 21 of their papers we have counts for
23 papers
UniBuc at SemEval-2024 Task 2: Tailored Prompting with Solar for Clinical NLI
Marius Micluta-Campeanu, Claudiu Creanga, Ana-Maria Bucur +2
This paper describes the approach of the UniBuc team in tackling the SemEval 2024 Task 2: Safe Biomedical Natural Language Inference for Clinical Trials. We used SOLAR Instruct, wi…
Last Translation Benchmark
Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…
Mental Health Disorder Detection Beyond Social Media: A Systematic Review of Available Datasets
Sadiya Sayara Chowdhury Puspo, Ana-Maria Bucur, Stevie Chancellor +2
Detecting mental health disorders in a timely manner is an important societal challenge. NLP and machine learning (ML) methods used to assist with detection rely on data collected…
PsihoRo: Depression and Anxiety Romanian Text Corpus
Alexandra Ciobotaru, Ana-Maria Bucur, Liviu P. Dinu
Psychological corpora in NLP are collections of texts used to analyze human psychology, emotions, and mental health. These texts allow researchers to study psychological constructs…
Assessing the Effectiveness of LLMs in Delivering Cognitive Behavioral Therapy
Navdeep Singh Bedi, Ana-Maria Bucur, Noriko Kando +1
As mental health issues continue to rise globally, there is an increasing demand for accessible and scalable therapeutic solutions. Many individuals currently seek support from Lar…
Large Language Models for Mental Health: A Multilingual Evaluation
Nishat Raihan, Sadiya Sayara Chowdhury Puspo, Ana-Maria Bucur +2
Large Language Models (LLMs) have remarkable capabilities across NLP tasks. However, their performance in multilingual contexts, especially within the mental health domain, has not…
A Survey on Multilingual Mental Disorders Detection from Social Media Data
Ana-Maria Bucur, Marcos Zampieri, Tharindu Ranasinghe +1
The increasing prevalence of mental disorders globally highlights the urgent need for effective digital screening methods that can be used in multilingual contexts. Most existing s…
Datasets for Depression Modeling in Social Media: An Overview
Ana-Maria Bucur, Andreea-Codrina Moldovan, Krutika Parvatikar +3
Depression is the most common mental health disorder, and its prevalence increased during the COVID-19 pandemic. As one of the most extensively researched psychological conditions,…
BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages
Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin +45
People worldwide use language in subtle and complex ways to express emotions. Although emotion recognition--an umbrella term for several NLP tasks--impacts various applications wit…
On the State of NLP Approaches to Modeling Depression in Social Media: A Post-COVID-19 Outlook
Ana-Maria Bucur, Andreea-Codrina Moldovan, Krutika Parvatikar +3
Computational approaches to predicting mental health conditions in social media have been substantially explored in the past years. Multiple reviews have been published on this top…
RoMath: A Mathematical Reasoning Benchmark in Romanian
Adrian Cosma, Ana-Maria Bucur, Emilian Radoi
Mathematics has long been conveyed through natural language, primarily for human understanding. With the rise of mechanized mathematics and proof assistants, there is a growing nee…
Reading Between the Frames: Multi-Modal Depression Detection in Videos from Non-Verbal Cues
David Gimeno-Gómez, Ana-Maria Bucur, Adrian Cosma +2
Depression, a prominent contributor to global disability, affects a substantial portion of the population. Efforts to detect depression from social media texts have been prevalent,…
Automatic Extraction of the Romanian Academic Word List: Data and Methods
Ana-Maria Bucur, Andreea Dincă, Mădălina Chitez +1
This paper presents the methodology and data used for the automatic extraction of the Romanian Academic Word List (Ro-AWL). Academic Word Lists are useful in both L2 and L1 teachin…
Utilizing ChatGPT Generated Data to Retrieve Depression Symptoms from Social Media
Ana-Maria Bucur
In this work, we present the contribution of the BLUE team in the eRisk Lab task on searching for symptoms of depression. The task consists of retrieving and ranking Reddit social…
It's Just a Matter of Time: Detecting Depression with Time-Enriched Multimodal Transformers
Ana-Maria Bucur, Adrian Cosma, Paolo Rosso +1
Depression detection from user-generated content on the internet has been a long-lasting topic of interest in the research community, providing valuable screening tools for psychol…
An End-to-End Set Transformer for User-Level Classification of Depression and Gambling Disorder
Ana-Maria Bucur, Adrian Cosma, Liviu P. Dinu +1
This work proposes a transformer architecture for user-level classification of gambling addiction and depression that is trainable end-to-end. As opposed to other methods that oper…
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,…
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…
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…
A Psychologically Informed Part-of-Speech Analysis of Depression in Social Media
Ana-Maria Bucur, Ioana R. Podină, Liviu P. Dinu
In this work, we provide an extensive part-of-speech analysis of the discourse of social media users with depression. Research in psychology revealed that depressed users tend to b…
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…
An Exploratory Analysis of the Relation Between Offensive Language and Mental Health
Ana-Maria Bucur, Marcos Zampieri, Liviu P. Dinu
In this paper, we analyze the interplay between the use of offensive language and mental health. We acquired publicly available datasets created for offensive language identificati…
Detecting Early Onset of Depression from Social Media Text using Learned Confidence Scores
Ana-Maria Bucur, Liviu P. Dinu
Computational research on mental health disorders from written texts covers an interdisciplinary area between natural language processing and psychology. A crucial aspect of this p…