KDD 2026 - AUDETER: A Large-scale Dataset for Deepfake Audio Detection in Open Worlds @TheOfficialACM
KDD 2026 - AUDETER: A Large-scale Dataset for Deepfake Audio Detection in Open Worlds @TheOfficialACM
Uploaded July 2026 | Updated September 2026, 2 weeks ago
Qizhou Wang, Hanxun Huang, Guansong Pang, Sarah Erfani, Christopher Leckie
KDD 2026 - AUDETER: A Large-scale Dataset for Deepfake Audio Detection in Open Worlds2025 Outstanding Contribution to ACM AwardKDD 2026 - Geometry-Preserving Supervised Biological Sequence DesignKDD2026-R-Select: A Robust Multi-Metric DataSelection Approach for Fine-Tuning Large Language ModelsKDD 2026 - Efficient Test-Time Scaling for LLM-based Time Series ForecastingKDD 2026 - PinRec: Unified Generative Retrieval Model for Pinterest Recommender Systems2025 ACM – AAAI Allen Newell AwardKDD 2026 - Orbit-Adaptive Zero-Shot Forecasting on Spatio-Temporal GraphKDD 2026 - PolarFormer: Radial-Angular Latent Modeling for Unconditional Time Series GenerationKDD 2026 - APEX-SQL: Talking to the data via Agentic Exploration for Text-to-SQLJPAL Summer of Science Poster Presentations (in Spanish)Fireside Chat with Entrepreneur/Venture Capitalist Vinod Khosla
Association for Computing Machinery (ACM) |

KDD 2026 - AUDETER: A Large-scale Dataset for Deepfake Audio Detection in Open Worlds

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