🔄 In a Training Loop
Mukul Ranjan
mukul54
P(doom) Rejects the premise
AI & ML interests
Efficiency, Optimization
Recent Activity
reacted to Parveshiiii's post with 🤗 2 days ago
Most deepfake audio detectors are quietly cheating.
They don’t really listen to the speech — they just look at how long the embedding vector is. Once they figure that out, accuracy looks great on paper and falls apart in the wild.
AIRealNet-Audio was built to stop that shortcut.
It forces every feature onto the unit hypersphere (twice) so the model can only use direction, not magnitude. Trained on speech from 100+ different TTS and voice-cloning systems, plus real human recordings under heavy compression and noise.
The result is a detector that actually has to learn the artifacts instead of gaming the feature space.
Model: https://huggingface.co/Modotte/AIRealNet-Audio authored a paper 2 days ago
AdvSim2Real : Training Web Agents Against Adaptive Prompt Injection in a Web World ModelOrganizations
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datasets 9
mukul54/tab-vlm
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mukul54/motion-text-classifier-v2
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mukul54/motion-text-classifier
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mukul54/spookybench-v2
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mukul54/culture-vlm-dataset-files
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mukul54/culture-vlm-artifact-dataset
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mukul54/LUAD_GSE131907
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mukul54/video_gpt_activitynet_test
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mukul54/video_chatgpt_activitynet_videos
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