| 2026 | ECIR | Forward Index Compression for Learned Sparse Retrieval. | Sebastian Bruch, Martino Fontana, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini |
| 2025 | ACL | Uncovering Visual-Semantic Psycholinguistic Properties from the Distributional Structure of Text Embedding Space. | Si Wu, Sebastian Bruch |
| 2025 | ECIR | Investigating the Scalability of Approximate Sparse Retrieval Algorithms to Massive Datasets. | Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini, Leonardo Venuta |
| 2025 | SIGIR | ReNeuIR at SIGIR 2025: The Fourth Workshop on Reaching Efficiency in Neural Information Retrieval. | Sebastian Bruch, Maik Frbe, Tim Hagen, Franco Maria Nardini, Martin Potthast |
| 2025 | WSDM | Advances in Vector Search. | Sebastian Bruch |
| 2024 | CIKM | Pairing Clustered Inverted Indexes with κ-NN Graphs for Fast Approximate Retrieval over Learned Sparse Representations. | Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini |
| 2024 | SIGIR | Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representations. | Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini |
| 2024 | SIGIR | A Learning-to-Rank Formulation of Clustering-Based Approximate Nearest Neighbor Search. | Thomas Vecchiato, Claudio Lucchese, Franco Maria Nardini, Sebastian Bruch |
| 2023 | KDD | Yggdrasil Decision Forests: A Fast and Extensible Decision Forests Library. | Mathieu Guillame-Bert, Sebastian Bruch, Richard Stotz, Jan Pfeifer |
| 2023 | SIGIR | ReNeuIR at SIGIR 2023: The Second Workshop on Reaching Efficiency in Neural Information Retrieval. | Sebastian Bruch, Joel Mackenzie, Maria Maistro, Franco Maria Nardini |
| 2023 | VECoS | Shielded Learning for Resilience and Performance Based on Statistical Model Checking in Simulink. | Julius Adelt, Sebastian Bruch, Paula Herber, Mathis Niehage, Anne Remke |
| 2022 | SIGIR | ReNeuIR: Reaching Efficiency in Neural Information Retrieval. | Sebastian Bruch, Claudio Lucchese, Franco Maria Nardini |
| 2021 | WWW | An Alternative Cross Entropy Loss for Learning-to-Rank. | Sebastian Bruch |
| 2020 | WSDM | A Stochastic Treatment of Learning to Rank Scoring Functions. | Sebastian Bruch, Shuguang Han, Michael Bendersky, Marc Najork |
| 2019 | ICTIR | Learning Groupwise Multivariate Scoring Functions Using Deep Neural Networks. | Qingyao Ai, Xuanhui Wang, Sebastian Bruch, Nadav Golbandi, Michael Bendersky, Marc Najork |
| 2019 | ICTIR | An Analysis of the Softmax Cross Entropy Loss for Learning-to-Rank with Binary Relevance. | Sebastian Bruch, Xuanhui Wang, Michael Bendersky, Marc Najork |
| 2019 | ICTIR | Neural Learning to Rank using TensorFlow Ranking: A Hands-on Tutorial. | Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang |
| 2019 | KDD | TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank. | Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork, Jan Pfeifer, Nadav Golbandi, Rohan Anil, Stephan Wolf |
| 2019 | SIGIR | Revisiting Approximate Metric Optimization in the Age of Deep Neural Networks. | Sebastian Bruch, Masrour Zoghi, Michael Bendersky, Marc Najork |
| 2019 | SIGIR | Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning. | Claudio Lucchese, Franco Maria Nardini, Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang, Harrie Oosterhuis, Rolf Jagerman, Maarten de Rijke |
| 2013 | ECIR | Training Efficient Tree-Based Models for Document Ranking. | Sebastian Bruch, Jimmy Lin |
| 2013 | KDD | Dynamic memory allocation policies for postings in real-time Twitter search. | Sebastian Bruch, Jimmy Lin, Michael Busch |
| 2013 | SIGIR | Effectiveness/efficiency tradeoffs for candidate generation in multi-stage retrieval architectures. | Sebastian Bruch, Jimmy Lin |
| 2012 | CIKM | Fast candidate generation for two-phase document ranking: postings list intersection with bloom filters. | Sebastian Bruch, Jimmy Lin |
| 2012 | WWW | Mr. LDA: a flexible large scale topic modeling package using variational inference in MapReduce. | Ke Zhai, Jordan L. Boyd-Graber, Sebastian Bruch, Mohamad L. Alkhouja |
| 2011 | SIGIR | Pseudo test collections for learning web search ranking functions. | Sebastian Bruch, Donald Metzler, Tamer Elsayed, Jimmy Lin |
| 2011 | SIGIR | Cross-corpus relevance projection. | Sebastian Bruch, Donald Metzler, Jimmy Lin |