EchoRec Enhances Generative Recommendation with Multi-Token Prediction and Cycle Consistency
_reachsumit · x · 2026-08-17
Core Method: EchoRec leverages Multi-Token Prediction (MTP) to forecast user actions and uses cycle-consistent preference alignment to verify the model's absorption of future behavior signals.
Architecture: Comprises two modules: 1) Horizon-aware Preference Generation (HPG): Chains auxiliary branches to model preference evolution sequentially. 2) Verifiable Holistic-Preference Alignment (VHA): Consolidates multi-horizon preferences and suppresses spurious alignment via cycle-consistent projectors.
Insight: Analysis reveals that future behaviors act as a "semantic echo" of current ones, decaying over intent transitions, serving as informative yet order-dependent supervision signals.
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