| Scale Calibration of Deep Ranking Models | 0 | 0.34 | 2022 |
| On Optimizing Top-K Metrics for Neural Ranking Models | 1 | 0.35 | 2022 |
| Graph Technologies for User Modeling and Recommendation: Introduction to the Special Issue - Part 1 | 0 | 0.34 | 2022 |
| Revisiting Two-tower Models for Unbiased Learning to Rank | 1 | 0.35 | 2022 |
| Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models | 0 | 0.34 | 2022 |
| Rax: Composable Learning-to-Rank Using JAX | 0 | 0.34 | 2022 |
| Introduction to the Special Section on Graph Technologies for User Modeling and Recommendation, Part 2 | 0 | 0.34 | 2022 |
| Bootstrapping Recommendations at Chrome Web Store | 1 | 0.35 | 2021 |
| Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees? | 0 | 0.34 | 2021 |
| Rethinking search: making domain experts out of dilettantes | 1 | 0.40 | 2021 |
| Glean: structured extractions from templatic documents | 0 | 0.34 | 2021 |
| Scalable Hierarchical Agglomerative Clustering | 0 | 0.34 | 2021 |
| Dynamic Language Models for Continuously Evolving Content | 1 | 0.43 | 2021 |
| Ensemble Distillation for BERT-Based Ranking Models. | 0 | 0.34 | 2021 |
| Improving Cloud Storage Search with User Activity | 0 | 0.34 | 2021 |
| Search And Discovery In Personal Email Collections | 0 | 0.34 | 2021 |
| Natural Language Understanding with Privacy-Preserving BERT | 0 | 0.34 | 2021 |
| Report on the 2nd international conference on design of experimental search & information retrieval systems (DESIRES 2021). | 0 | 0.34 | 2021 |
| Glean: Structured Extractions from Templatic Documents. | 0 | 0.34 | 2021 |
| Feature Transformation for Neural Ranking Models | 2 | 0.38 | 2020 |
| Migrating a Privacy-Safe Information Extraction System to a Software 2.0 Design. | 0 | 0.34 | 2020 |
| Learning to Cluster Documents into Workspaces Using Large Scale Activity Logs | 0 | 0.34 | 2020 |
| Representation Learning for Information Extraction from Form-like Documents | 1 | 0.35 | 2020 |
| Permutation Equivariant Document Interaction Network for Neural Learning to Rank | 2 | 0.35 | 2020 |
| Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Long-Form Document Matching | 3 | 0.42 | 2020 |
| Adversarial Bandits Policy for Crawling Commercial Web Content | 0 | 0.34 | 2020 |
| Predictive Crawling for Commercial Web Content | 0 | 0.34 | 2019 |
| Revisiting Approximate Metric Optimization in the Age of Deep Neural Networks | 8 | 0.50 | 2019 |
| Online Template Induction for Machine-Generated Emails. | 0 | 0.34 | 2019 |
| Semantic Text Matching for Long-Form Documents | 5 | 0.41 | 2019 |
| Addressing Trust Bias for Unbiased Learning-to-Rank | 7 | 0.41 | 2019 |
| RiSER: Learning Better Representations for Richly Structured Emails | 1 | 0.35 | 2019 |
| Uncovering Hidden Structure in Sequence Data via Threading Recurrent Models. | 0 | 0.34 | 2019 |
| Multi-view Embedding-based Synonyms for Email Search | 3 | 0.38 | 2019 |
| Online Template Induction for Machine-Generated Emails. | 0 | 0.34 | 2019 |
| Position Bias Estimation for Unbiased Learning to Rank in Personal Search. | 33 | 0.90 | 2018 |
| Semantic Location in Email Query Suggestion. | 0 | 0.34 | 2018 |
| Anatomy of a Privacy-Safe Large-Scale Information Extraction System Over Email | 0 | 0.34 | 2018 |
| Offline Comparison of Ranking Functions using Randomized Data. | 0 | 0.34 | 2018 |
| Learning with Sparse and Biased Feedback for Personal Search. | 0 | 0.34 | 2018 |
| Hidden in Plain Sight: Classifying Emails Using Embedded Image Contents. | 1 | 0.35 | 2018 |
| Training On-Device Ranking Models from Cross-User Interactions in a Privacy-Preserving Fashion. | 0 | 0.34 | 2018 |
| TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank. | 9 | 0.49 | 2018 |
| The LambdaLoss Framework for Ranking Metric Optimization. | 13 | 0.53 | 2018 |
| Learning Groupwise Scoring Functions Using Deep Neural Networks. | 3 | 0.38 | 2018 |
| Quick Access: Building a Smart Experience for Google Drive | 7 | 0.44 | 2017 |
| Learning from User Interactions in Personal Search via Attribute Parameterization. | 14 | 0.55 | 2017 |
| Using Machine Learning to Improve the Email Experience | 2 | 0.36 | 2016 |
| Learning to Rank with Selection Bias in Personal Search. | 47 | 1.19 | 2016 |
| Debugging a Crowdsourced Task with Low Inter-Rater Agreement | 5 | 0.47 | 2015 |
