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HAIM: Human-AI Music Datasets for AI Music Production Tracking Benchmark
arXiv:2606.01686v1 Announce Type: new Abstract: As generative platforms such as Suno and Udio reach human-grade audio quality, the scope of AI's utility has expanded across the entire music production workflow. Beyond simple track generation, these advancements have catalyzed the adoption of AI-driven methodologies in diverse forms. These include vocal synthesis, arrangement, and professional mastering.
AI music startup Suno raises funding at $5.4 billion valuation
AI music startup Suno raises funding at $5.4 billion valuation June 3 : Suno said on Wednesday it has raised more than $400 million in a funding round at a $5.4 billion valuation, as the AI music startup looks to enhance its platform by creating new tools. Here are some details: • The Massachusetts-based startup, which allows users to generate songs via AI prompts, said Bond Capital led the Series D funding round alongside venture capital firms such as IVP, Forerunner and Union Square...
AI is blowing up music. How should the Grammys handle it?
Today I’m talking with Harvey Mason Jr., who is CEO of the Recording Academy — that’s the outfit that puts on the Grammy Awards. I last talked to Harvey in 2024, when it was obvious that generative AI would upend the music industry, but still not exactly clear how that would happen. Well, it’s been 18 months since that conversation, and you’re going to hear Harvey say that AI is now “omnipresent” in music production. And Harvey knows what he’s talking about — he is himself a legendary...
APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music
Announce Type: replace Abstract: Music popularity prediction has attracted growing research interest, with relevance to artists, platforms, and recommendation systems. However, the explosive rise of AI-generated music platforms has created an entirely new and largely unexplored landscape, where a surge of songs is produced and consumed daily without the traditional markers of artist reputation or label backing. Key, yet unexplored in this pursuit is aesthetic quality.
Probing Token Spaces under Generator Shift in AI-Generated Music Detection
arXiv:2606.08663v1 Announce Type: new Abstract: AI-generated music detectors can appear robust on standard benchmark splits, yet their deployments require transfer to generator sources absent during training. We study this problem with source-restricted evaluation on \textsc{MoM-open}, an open reconstruction of MoM-CLAM that replaces the non-redistributable real corpus with FMA and MTG-Jamendo while preserving the fake-generator protocol. To isolate the role of representation, we introduce...
SARA: Stress Test Reasoning in Audio Deepfake Detection
arXiv:2601.03615v2 Announce Type: replace Abstract: Audio Language Models (ALMs) offer a promising shift towards explainable audio deepfake detections (ADD), moving beyond \textit{black-box} classifiers by providing transparency to their predictions via reasoning traces. However, such reasoning may not support the model predictions, reflecting poor coherence, or, worse, may rationalize incorrect predictions with plausible but misleading explanation. Moreover, the behavior of ALM reasoning...
SMART: Shot-Aware Multimodal Video Moment Retrieval with Audio-Enhanced MLLM
arXiv:2511.14143v2 Announce Type: replace Abstract: Video Moment Retrieval is a task in video understanding that aims to localize a specific temporal segment in an untrimmed video based on a natural language query. Despite recent progress in moment retrieval from videos using both traditional techniques and Multimodal Large Language Models (MLLM), most existing methods still rely on coarse temporal understanding and a single visual modality, limiting performance on complex videos. To address...