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Bid Farewell to Seesaw: New Framework Boosts Long-Tail Recommendation Accuracy Without Sacrificing Diversity Technology
Artificial Intelligence #session-based recommendation#long-tail

Bid Farewell to Seesaw: New Framework Boosts Long-Tail Recommendation Accuracy Without Sacrificing Diversity

A new research paper from arxiv introduces HID (Hybrid Intent-based Dual Constraint Framework), a plug-and-play solution for session-based recommendation that simultaneously improves recommendation accuracy and long-tail item performance, eliminating the traditional trade-off. The framework uses hybrid intent learning and intent constraint loss to filter session-irrelevant noise.

Jul 8, 2026 1 source