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.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.IR 1years
2026 1verdicts
ACCEPT 1representative citing papers
citing papers explorer
-
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.