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Ditch the noise: FAVE achieves 10x faster sequential recommendations by learning a direct, one-step trajectory from user history to predicted item, bypassing the inefficient "noise-to-data" paradigm.
Achieve up to 55.7% token reduction and 4.1% accuracy improvement in language reasoning by selectively compressing reasoning traces, proving that less can be more.
