From the 1 of 6 linked papers with an AI index.
6 papers
Detect Early, Escalate Rarely: Anytime Detection of AI-Generated Video from the Compressed Bitstream
Mert Onur Cakiroglu, Mehmet Dalkilic, Hasan Kurban
Detectors for AI-generated video are evaluated offline. A clip is decoded to pixels and scored once, increasingly by a large vision-language model. Detection, however, is deployed…
The Spectrum Is Not Enough: When Context Helps Time-Series Forecasting
Mert Onur Cakiroglu, Mehmet Dalkilic, Hasan Kurban
The paper shows that indices based only on a time series' power spectrum cannot predict the benefit of adding contextual information such as longer lookbacks, retrieval modules, or…
LGQ: Learnable Geometric Quantization for Image Tokenization
Idil Bilge Altun, Mert Onur Cakiroglu, Elham Buxton +2
Recent collapse-free quantizers such as FSQ achieve stable training by replacing the learnable codebook with an engineered geometry: a fixed scalar grid whose structure is dictated…
Auditing Generalization in AI-Generated Video Detection: A Six-Control Protocol and the VidAudit Toolkit
Mert Onur Cakiroglu, Zhihe Lu, Mehmet Dalkilic +1
AI-generated video detection benchmarks such as GenVidBench and AIGVDBench are the de facto leaderboards, yet most evaluation protocols leave uncontrolled confounds that can inflat…
Temporal Realism Evaluation of Generated Videos Using Compressed-Domain Motion Vectors
Mert Onur Cakiroglu, Idil Bilge Altun, Zhihe Lu +2
Temporal realism remains a central weakness of current generative video models, as most evaluation metrics prioritize spatial appearance and offer limited sensitivity to motion. We…
Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting
Mert Onur Cakiroglu, Idil Bilge Altun, Mehmet Dalkilic +2
Time series forecasting remains a challenging task for foundation models due to temporal heterogeneity, high dimensionality, and the lack of inherent symbolic structure. In this wo…