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AI-AI co-creation can generate more creative and novel ideas than human pairs, reshaping our understanding of collaborative creativity in AI.
Achieving a remarkable 1.454% EER, Teffic-Audio outshines all public competitors in the challenging landscape of speech deepfake detection.
UMMs struggle with cross-modal consistency not from a lack of shared representations, but from misaligned latent space transformations, which LatentUMM fixes.
Robot manipulation models trained on mostly VR data can perform as well as those trained on real-world data, but at 1/20th the cost.
Stop reimplementing multimodal models: TorchUMM offers a unified codebase for evaluation, analysis, and post-training, streamlining research across diverse architectures and tasks.
