20 citations · 75 across the 20 of their papers we have counts for
23 papers
Prompt or Policy? Optimizing Physician Slate Presentations with LLM User Simulators
Andrei Niculae, Adrian Cosma, Emilian Radoi
Choosing the right physician is a key challenge for patients seeking medical care. Physician recommendation systems identify relevant doctors, but patients still find it difficult…
On Model and Data Scaling for Skeleton-based Self-Supervised Gait Recognition
Adrian Cosma, Andy Cǎtrunǎ, Emilian Rǎdoi
Gait recognition from video streams is a challenging problem in computer vision biometrics due to the subtle differences between gaits and numerous confounding factors. Recent adva…
How Hard is this Test Set? NLI Characterization by Exploiting Training Dynamics
Adrian Cosma, Stefan Ruseti, Mihai Dascalu +1
Natural Language Inference (NLI) evaluation is crucial for assessing language understanding models; however, popular datasets suffer from systematic spurious correlations that arti…
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…
RoCode: A Dataset for Measuring Code Intelligence from Problem Definitions in Romanian
Adrian Cosma, Bogdan Iordache, Paolo Rosso
Recently, large language models (LLMs) have become increasingly powerful and have become capable of solving a plethora of tasks through proper instructions in natural language. How…
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,…
GaitFormer: Learning Gait Representations with Noisy Multi-Task Learning
Adrian Cosma, Emilian Radoi
Gait analysis is proven to be a reliable way to perform person identification without relying on subject cooperation. Walking is a biometric that does not significantly change in s…
Learning to Simplify Spatial-Temporal Graphs in Gait Analysis
Adrian Cosma, Emilian Radoi
Gait analysis leverages unique walking patterns for person identification and assessment across multiple domains. Among the methods used for gait analysis, skeleton-based approache…
PsyMo: A Dataset for Estimating Self-Reported Psychological Traits from Gait
Adrian Cosma, Emilian Radoi
Psychological trait estimation from external factors such as movement and appearance is a challenging and long-standing problem in psychology, and is principally based on the psych…
GaitPT: Skeletons Are All You Need For Gait Recognition
Andy Catruna, Adrian Cosma, Emilian Radoi
The analysis of patterns of walking is an important area of research that has numerous applications in security, healthcare, sports and human-computer interaction. Lately, walking…
GaitMorph: Transforming Gait by Optimally Transporting Discrete Codes
Adrian Cosma, Emilian Radoi
Gait, the manner of walking, has been proven to be a reliable biometric with uses in surveillance, marketing and security. A promising new direction for the field is training gait…
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…
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…
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…
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…
WildGait: Learning Gait Representations from Raw Surveillance Streams
Adrian Cosma, Emilian Radoi
The use of gait for person identification has important advantages such as being non-invasive, unobtrusive, not requiring cooperation and being less likely to be obscured compared…
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…
A Generic and Model-Agnostic Exemplar Synthetization Framework for Explainable AI
Antonio Barbalau, Adrian Cosma, Radu Tudor Ionescu +1
With the growing complexity of deep learning methods adopted in practical applications, there is an increasing and stringent need to explain and interpret the decisions of such met…
Self-Supervised Representation Learning on Document Images
Adrian Cosma, Mihai Ghidoveanu, Michael Panaitescu-Liess +1
This work analyses the impact of self-supervised pre-training on document images in the context of document image classification. While previous approaches explore the effect of se…
CamLoc: Pedestrian Location Detection from Pose Estimation on Resource-constrained Smart-cameras
Adrian Cosma, Ion Emilian Radoi, Valentin Radu
Recent advancements in energy-efficient hardware technology is driving the exponential growth we are experiencing in the Internet of Things (IoT) space, with more pervasive computa…