DADF adds a plug-in second-stage debiasing layer with dynamic target transformation, duration-aware residual modeling, and multi-label auxiliary signals to reduce local calibration errors in long-tailed watch-time regression.
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Intermediate decoder hidden states from frozen LVLMs fused with ID embeddings outperform caption representations and deliver state-of-the-art micro-video recommendation performance on two real-world benchmarks.
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DADF: A Distribution-Aware Debiasing Framework for Watch-Time Regression in Recommender Systems
DADF adds a plug-in second-stage debiasing layer with dynamic target transformation, duration-aware residual modeling, and multi-label auxiliary signals to reduce local calibration errors in long-tailed watch-time regression.
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Frozen LVLMs for Micro-Video Recommendation: A Systematic Study of Feature Extraction and Fusion
Intermediate decoder hidden states from frozen LVLMs fused with ID embeddings outperform caption representations and deliver state-of-the-art micro-video recommendation performance on two real-world benchmarks.