9 citations · 21 across the 42 of their papers we have counts for
17 papers · 1 filter
Machine Unlearning in the Era of Quantum Machine Learning: An Empirical Study
Carla Crivoi, Radu Tudor Ionescu
We present the first empirical study of machine unlearning (MU) in hybrid quantum-classical neural networks. While MU has been extensively explored in classical deep learning, its…
AutoMalDesc: Large-Scale Script Analysis for Cyber Threat Research
Alexandru-Mihai Apostu, Andrei Preda, Alexandra Daniela Damir +4
Generating thorough natural language explanations for threat detections remains an open problem in cybersecurity research, despite significant advances in automated malware detecti…
Every Character Counts: From Vulnerability to Defense in Phishing Detection
Maria Chiper, Radu Tudor Ionescu
Phishing attacks targeting both organizations and individuals are becoming an increasingly significant threat as technology advances. Current automatic detection methods often lack…
PRNU-Bench: A Novel Benchmark and Model for PRNU-Based Camera Identification
Florinel Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu
We propose a novel benchmark for camera identification via Photo Response Non-Uniformity (PRNU) estimation. The benchmark comprises 13K photos taken with 120+ cameras, where the tr…
Curriculum Multi-Task Self-Supervision Improves Lightweight Architectures for Onboard Satellite Hyperspectral Image Segmentation
Hugo Carlesso, Josiane Mothe, Radu Tudor Ionescu
Hyperspectral imaging (HSI) captures detailed spectral signatures across hundreds of contiguous bands per pixel, being indispensable for remote sensing applications such as land-co…
A Large-Scale Benchmark for Evaluating Large Language Models on Medical Question Answering in Romanian
Ana-Cristina Rogoz, Radu Tudor Ionescu, Alexandra-Valentina Anghel +3
We introduce MedQARo, the first large-scale medical QA benchmark in Romanian, alongside a comprehensive evaluation of state-of-the-art large language models (LLMs). We construct a…
AIM 2025 Rip Current Segmentation (RipSeg) Challenge Report
Andrei Dumitriu, Florin Miron, Florin Tatui +24
This report presents an overview of the AIM 2025 RipSeg Challenge, a competition designed to advance techniques for automatic rip current segmentation in still images. Rip currents…
SlotMatch: Distilling Object-Centric Representations for Unsupervised Video Segmentation
Diana-Nicoleta Grigore, Neelu Madan, Andreas Mogelmose +2
Unsupervised video segmentation is a challenging computer vision task, especially due to the lack of supervisory signals coupled with the complexity of visual scenes. To overcome t…
GeMix: Conditional GAN-Based Mixup for Improved Medical Image Augmentation
Hugo Carlesso, Maria Eliza Patulea, Moncef Garouani +2
Mixup has become a popular augmentation strategy for image classification, yet its naive pixel-wise interpolation often produces unrealistic images that can hinder learning, partic…
XMAD-Bench: Cross-Domain Multilingual Audio Deepfake Benchmark
Ioan-Paul Ciobanu, Andrei-Iulian Hiji, Nicolae-Catalin Ristea +3
Recent advances in audio generation led to an increasing number of deepfakes, making the general public more vulnerable to financial scams, identity theft, and misinformation. Audi…
MAVOS-DD: Multilingual Audio-Video Open-Set Deepfake Detection Benchmark
Florinel-Alin Croitoru, Vlad Hondru, Marius Popescu +3
We present the first large-scale open-set benchmark for multilingual audio-video deepfake detection. Our dataset comprises nearly 350 hours of real and fake videos across eight lan…
RipVIS: Rip Currents Video Instance Segmentation Benchmark for Beach Monitoring and Safety
Andrei Dumitriu, Florin Tatui, Florin Miron +3
Rip currents are strong, localized and narrow currents of water that flow outwards into the sea, causing numerous beach-related injuries and fatalities worldwide. Accurate identifi…
Detecting and Mitigating DDoS Attacks with AI: A Survey
Alexandru Apostu, Silviu Gheorghe, Andrei Hîji +5
Distributed Denial of Service attacks represent an active cybersecurity research problem. Recent research shifted from static rule-based defenses towards AI-based detection and mit…
ExDDV: A New Dataset for Explainable Deepfake Detection in Video
Vlad Hondru, Eduard Hogea, Darian Onchis +1
The ever growing realism and quality of generated videos makes it increasingly harder for humans to spot deepfake content, who need to rely more and more on automatic deepfake dete…
Text Classification Under Class Distribution Shift: A Survey
Adriana Valentina Costache, Silviu Florin Gheorghe, Eduard Gabriel Poesina +2
The basic underlying assumption of machine learning (ML) models is that the training and test data are sampled from the same distribution. However, in daily practice, this assumpti…
Task-Informed Anti-Curriculum by Masking Improves Downstream Performance on Text
Andrei Jarca, Florinel Alin Croitoru, Radu Tudor Ionescu
Masked language modeling has become a widely adopted unsupervised technique to pre-train large language models (LLMs). However, the process of selecting tokens for masking is rando…
Large Multimodal Models for Low-Resource Languages: A Survey
Marian Lupascu, Ana-Cristina Rogoz, Mihai Sorin Stupariu +1
In this survey, we systematically analyze techniques used to adapt large multimodal models (LMMs) for low-resource (LR) languages, examining approaches ranging from visual enhancem…