activity
20242026
most citedDeepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook

2 citations · 2 across the 7 of their papers we have counts for

collaborators

38 papers

cs.CV2026

DF-MoE: Generalizable Deepfake Detection via Multimodal Sparse Mixture-of-Experts

Vlad Hondru, Florinel Alin Croitoru, Iuliana Georgescu +2

Audio-visual deepfake detection is an actively studied topic, where one of the main challenges is to develop detectors able to generalize across deepfake generation methods. We con…

cs.CL2026

Audio Sentiment Analysis via Distillation and Cross-Modal Integration of Generated Multilingual Transcripts

Andrei-George Durdun, Victor Constantinescu, Radu Tudor Ionescu

Automatically recognizing the sentiment, positive or negative, from speech is a challenging task, requiring both the analysis of vocal inflections and the interpretation of uttered…

cs.CV20262 cited

Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook

Florinel-Alin Croitoru, Andrei-Iulian Hiji, Vlad Hondru +7

We survey deepfake generation and detection techniques, covering all deepfake media types: image, video, audio and multimodal content. We identify various kinds of deepfakes and co…

cs.CR2026

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…

cs.CL2026

Multilingual Coreference Resolution via Cycle-Consistent Machine Translation

Adriana-Valentina Costache, Eduard Poesina, Silviu-Florin Gheorghe +2

Coreference resolution is a core NLP task, having a broad range of downstream applications, e.g.~machine translation, question answering, document summarization, etc. While the tas…

cs.CV2026

MTL-MAD: Multi-Task Learners are Effective Medical Anomaly Detectors

Bogdan Alexandru Bercean, Florinel Alin Croitoru, Vlad Hondru +3

Anomaly detection in medical images is a challenging task, since anomalies are not typically available during training. Recent methods leverage a single pretext task coupled with a…