Despite the development of ranking optimization techniques, pointwise loss remains the dominating approach for click-through rate prediction. It can be attributed to the calibration ability of the pointwise loss since the prediction can be viewed as the click probability. In practice, a CTR prediction model is also commonly assessed with the ranking ability. To optimize the ranking ability, ranking loss (e.g., pairwise or listwise loss) can be adopted as they usually achieve better rankings than pointwise loss. Previous studies have experimented with a direct combination of the two losses to obtain the benefit from both losses and observed an improved performance. However, previous studies break the meaning of output logit as the click-through rate, which may lead to sub-optimal solutions. To address this issue, we propose an approach that can Jointly optimize the Ranking and Calibration abilities (JRC for short). JRC improves the ranking ability by contrasting the logit value for the sample with different labels and constrains the predicted probability to be a function of the logit subtraction. We further show that JRC consolidates the interpretation of logits, where the logits model the joint distribution. With such an interpretation, we prove that JRC approximately optimizes the contextualized hybrid discriminative-generative objective. Experiments on public and industrial datasets and online A/B testing show that our approach improves both ranking and calibration abilities. Since May 2022, JRC has been deployed on the display advertising platform of Alibaba and has obtained significant performance improvements.

翻译：尽管排序优化技术不断发展，逐点损失仍然是点击率预测的主流方法。这归因于逐点损失的校准能力，因为预测结果可被解释为点击概率。在实际应用中，CTR预测模型也通常通过排序能力进行评估。为优化排序能力，可采用排序损失（例如成对或列表式损失），因为它们通常比逐点损失获得更好的排序效果。先前研究尝试直接组合这两种损失以获取双方优势，并观察到性能提升。然而，这些研究破坏了输出logit作为点击率的意义，可能导致次优解。为解决此问题，我们提出一种能够联合优化排序与校准能力的方法（简称JRC）。JRC通过对比不同标签样本的logit值来增强排序能力，并将预测概率约束为logit差值函数。我们进一步证明，JRC巩固了logit的解释性，即logit建模联合分布。基于此解释，我们证明JRC近似优化了上下文混合判别-生成目标。在公共数据集、工业数据集及在线A/B测试上的实验表明，我们的方法同时提升了排序与校准能力。自2022年5月起，JRC已部署于阿里巴巴展示广告平台，并取得显著性能提升。