Efficiently teaching an effective dense retriever with balanced topic aware sampling S Hofstätter, SC Lin, JH Yang, J Lin, A Hanbury Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 316 | 2021 |
Improving efficient neural ranking models with cross-architecture knowledge distillation S Hofstätter, S Althammer, M Schröder, M Sertkan, A Hanbury arXiv preprint arXiv:2010.02666, 2020 | 195 | 2020 |
Local self-attention over long text for efficient document retrieval S Hofstätter, H Zamani, B Mitra, N Craswell, A Hanbury Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 88 | 2020 |
Interpretable & time-budget-constrained contextualization for re-ranking S Hofstätter, M Zlabinger, A Hanbury ECAI 2020, 513-520, 2020 | 85 | 2020 |
Let's measure run time! Extending the IR replicability infrastructure to include performance aspects S Hofstätter, A Hanbury Proceedings of the Open-Source IR Replicability Challenge (OSIRRC 2019) co …, 2019 | 52* | 2019 |
Intra-document cascading: Learning to select passages for neural document ranking S Hofstätter, B Mitra, H Zamani, N Craswell, A Hanbury Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 43 | 2021 |
On the Effect of Low-Frequency Terms on Neural-IR Models S Hofstätter, N Rekabsaz, C Eickhoff, A Hanbury Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019 | 40 | 2019 |
Fid-light: Efficient and effective retrieval-augmented text generation S Hofstätter, J Chen, K Raman, H Zamani Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | 34 | 2023 |
Introducing neural bag of whole-words with colberter: Contextualized late interactions using enhanced reduction S Hofstätter, O Khattab, S Althammer, M Sertkan, A Hanbury Proceedings of the 31st ACM International Conference on Information …, 2022 | 28 | 2022 |
Conformer-kernel with query term independence for document retrieval B Mitra, S Hofstatter, H Zamani, N Craswell arXiv preprint arXiv:2007.10434, 2020 | 28 | 2020 |
Mitigating the position bias of transformer models in passage re-ranking S Hofstätter, A Lipani, S Althammer, M Zlabinger, A Hanbury Advances in Information Retrieval: 43rd European Conference on IR Research …, 2021 | 18 | 2021 |
Cross-domain retrieval in the legal and patent domains: a reproducibility study S Althammer, S Hofstätter, A Hanbury Advances in Information Retrieval: 43rd European Conference on IR Research …, 2021 | 18 | 2021 |
TU Wien@ TREC Deep Learning'19--Simple Contextualization for Re-ranking S Hofstätter, M Zlabinger, A Hanbury arXiv preprint arXiv:1912.01385, 2019 | 18 | 2019 |
Enriching word embeddings for patent retrieval with global context S Hofstätter, N Rekabsaz, M Lupu, C Eickhoff, A Hanbury Advances in Information Retrieval: 41st European Conference on IR Research …, 2019 | 18 | 2019 |
PARM: A paragraph aggregation retrieval model for dense document-to-document retrieval S Althammer, S Hofstätter, M Sertkan, S Verberne, A Hanbury European Conference on Information Retrieval, 19-34, 2022 | 16 | 2022 |
Establishing strong baselines for tripclick health retrieval S Hofstätter, S Althammer, M Sertkan, A Hanbury European Conference on Information Retrieval, 144-152, 2022 | 12 | 2022 |
Linguistically informed masking for representation learning in the patent domain S Althammer, M Buckley, S Hofstätter, A Hanbury arXiv preprint arXiv:2106.05768, 2021 | 11 | 2021 |
Fine-grained relevance annotations for multi-task document ranking and question answering S Hofstätter, M Zlabinger, M Sertkan, M Schröder, A Hanbury Proceedings of the 29th ACM International Conference on Information …, 2020 | 10 | 2020 |
Multi-Task Retrieval-Augmented Text Generation with Relevance Sampling S Hofstätter, J Chen, K Raman, H Zamani ICML 2022 Workshop on Knowledge Retrieval and Language Models (KRLM @ ICML ’22), 2022 | 8 | 2022 |
Rank-without-GPT: Building GPT-Independent Listwise Rerankers on Open-Source Large Language Models X Zhang, S Hofstätter, P Lewis, R Tang, J Lin arXiv preprint arXiv:2312.02969, 2023 | 7 | 2023 |