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

2 citations · 2 across the 1 of their papers we have counts for

collaborators

11 papers

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.RO2026

Real-time tightly coupled GNSS and IMU integration via Factor Graph Optimization

Radu-Andrei Cioaca, Paul Irofti, Cristian Rusu +3

Reliable positioning in dense urban environments remains challenging due to frequent GNSS signal blockage, multipath, and rapidly varying satellite geometry. While factor graph opt…

cs.RO2026

Real-time loosely coupled GNSS and IMU integration via Factor Graph Optimization

Radu-Andrei Cioaca, Cristian Rusu, Paul Irofti +3

Accurate positioning, navigation, and timing (PNT) is fundamental to the operation of modern technologies and a key enabler of autonomous systems. A very important component of PNT…

cs.CL2026

MOSLD-Bench: Multilingual Open-Set Learning and Discovery Benchmark for Text Categorization

Adriana-Valentina Costache, Daria-Nicoleta Dragomir, Silviu-Florin Gheorghe +3

Open-set learning and discovery (OSLD) is a challenging machine learning task in which samples from new (unknown) classes can appear at test time. It can be seen as a generalizatio…