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cs.LG2026
MARCO: Click-Intent Decomposition for Calibrated Ads Conversion Prediction
Shiwen Shen, Xiru Huang, Liang Luo +32
Not all clicks are equal. Industrial ads ranking decouples conversion probability into click-through rate (CTR) and post-click conversion rate (CVR), yet treats every click as the…
cs.LG2026
TALAN: Task-Aligned Latent Adaptation Networks for Targeted Post-Training of Large Language Models
Chengkai Zhang, Ziteng Liu, Junpu Wang +4
Targeted post-training aims to improve reasoning, math, and code without degrading strengths. Low-rank adapters are efficient but task-global; activation interventions are input-aw…
cs.LG2025
Improving Large-Scale Recommender Systems with Auxiliary Learning
Mertcan Cokbas, Ziteng Liu, Zeyi Tao +10
Training large-scale recommendation models under a single global objective implicitly assumes homogeneity across user populations. However, real-world data are composites of hetero…