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 # Pointwise MonoBERT trained on Baidu-ULTR with Inverse Propensity Scoring (IPS)
-A flax-based MonoBERT cross encoder trained on the [Baidu-ULTR](https://arxiv.org/abs/2207.03051) dataset with the pointwise sigmoid cross-entropy loss with IPS correction suggested by [Bekker et al.](https://arxiv.org/abs/1809.03207) and [Saito et al.](https://arxiv.org/abs/1909.03601). The loss uses inverse propensity scoring to mitigate position bias in click data by weighting clicks on items higher that are less likely to be observed by users. For more info, [read our paper](https://arxiv.org/abs/2404.02543) and [find the code for this model here](https://github.com/philipphager/baidu-bert-model).
+A flax-based MonoBERT cross encoder trained on the [Baidu-ULTR](https://arxiv.org/abs/2207.03051) dataset with the **pointwise sigmoid cross-entropy loss with IPS correction** suggested by [Bekker et al.](https://arxiv.org/abs/1809.03207) and [Saito et al.](https://arxiv.org/abs/1909.03601). The loss uses inverse propensity scoring to mitigate position bias in click data by weighting clicks on items higher that are less likely to be observed by users. For more info, [read our paper](https://arxiv.org/abs/2404.02543) and [find the code for this model here](https://github.com/philipphager/baidu-bert-model).
 
 ## Test Results on Baidu-ULTR Expert Annotations