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A self-evolving memory paradigm for generative recommendation is proposed, aiming to enable effective evolution across heterogeneous behavioral patterns, and three key principles for effective self-evolving recommendation systems are identified, including isolated memorization, reinforced evolution, and scalable application.
PACodec slashes bitrate by 30% while preserving decoding quality, thanks to its innovative parallel quantization approach.
Dual time-frequency spectral representations can dramatically enhance the quality of degraded music recordings, outperforming traditional methods in both objective metrics and listener satisfaction.
Self-verification in SVR-R1 not only boosts multimodal reasoning accuracy but also reduces the need for extensive verification, showcasing a path to more confident model outputs.
