8 papers
Explainable Deepfake Detection Challenge
Abhijeet Narang, Kartik Kuckreja, Shreya Ghosh +4
Deepfake detection is moving beyond binary classification decisions toward systems that can also explain the visual evidence supporting those decisions. This transition is importan…
XPlainVerse: A Million-Scale Benchmark for Explainable Deepfake Detection
Abhijeet Narang, Kartik Kuckreja, Shreya Ghosh +3
As deepfake detection models increasingly produce natural language explanations, their reasoning often remains weakly grounded in visual artifacts, limiting reliability and user tr…
Objects Before Words: Object-First Inductive Biases for Grounding Language in Child-View Video
Sathira Silva, Abrham Kahsay Gebreselasie, Muhammad Umer Sheikh +3
Learning grounded word meaning from natural experience requires resolving two ambiguities in infant-view recordings: when the named referent appears and where it is in a cluttered…
Pixels Don't Lie (But Your Detector Might): Bootstrapping MLLM-as-a-Judge for Trustworthy Deepfake Detection and Reasoning Supervision
Kartik Kuckreja, Parul Gupta, Muhammad Haris Khan +1
Deepfake detection models often generate natural-language explanations, yet their reasoning is frequently ungrounded in visual evidence, limiting reliability. Existing evaluations…
AV-Deepfake1M++: A Large-Scale Audio-Visual Deepfake Benchmark with Real-World Perturbations
Zhixi Cai, Kartik Kuckreja, Shreya Ghosh +5
The rapid surge of text-to-speech and face-voice reenactment models makes video fabrication easier and highly realistic. To encounter this problem, we require datasets that rich in…
Tell me Habibi, is it Real or Fake?
Kartik Kuckreja, Parul Gupta, Injy Hamed +3
Deepfake generation methods are evolving fast, making fake media harder to detect and raising serious societal concerns. Most deepfake detection and dataset creation research focus…