| A completely reimplemented MPI bioinformatics toolkit with a new HHpred server at its core L Zimmermann, A Stephens, SZ Nam, D Rau, J Kübler, M Lozajic, ... Journal of molecular biology 430 (15), 2237-2243, 2018 | 2232 | 2018 |
| How Different are Pre-trained Transformers for Text Ranking? D Rau, J Kamps European Conference on Information Retrieval, 207-214, 2022 | 17 | 2022 |
| On the Realization of Compositionality in Neural Networks J Baan, J Leible, M Nikolaus, D Rau, D Ulmer, T Baumgärtner, D Hupkes, ... BlackboxNLP 2019, ACL, 2019 | 17 | 2019 |
| The Role of Complex NLP in Transformers for Text Ranking? D Rau, J Kamps ACM SIGIR International Conference on the Theory of Information Retrieval, 2022 | 14 | 2022 |
| Point-less: More Abstractive Summarization with Pointer-Generator Networks F Boutkan, J Ranzijn, D Rau, E van der Wel arXiv preprint arXiv:1905.01975, 2019 | 13 | 2019 |
| Impact of Tokenization, Pretraining Task, and Transformer Depth on Text Ranking J Kamps, N Kondylidis, D Rau Gaithersburg, MDNational Institute for Standards and Technology (NIST), 2021 | 7 | 2021 |
| University of Amsterdam at the CLEF 2022 SimpleText Track F Mostert, A Sampatsing, M Spronk, R David, J Kamps Proceedings of the Working Notes of CLEF, 2022 | 6 | 2022 |
| Context Embeddings for Efficient Answer Generation in RAG D Rau, S Wang, H Déjean, S Clinchant arXiv preprint arXiv:2407.09252, 2024 | 2 | 2024 |
| Revisiting Bag of Words Document Representations for Efficient Ranking with Transformers D Rau, M Dehghani, J Kamps ACM Transactions on Information Systems 42 (5), 1-27, 2024 | 2 | 2024 |
| LLM-based Retrieval and Generation Pipelines for TREC Interactive Knowledge Assistance Track (iKAT) 2023 Z Abbasiantaeb, C Meng, D Rau, A Krasakis, HA Rahmani, M Aliannejadi TREC, 2023 | 2 | 2023 |
| University of Amsterdam at TREC 2020: Deep Learning Track D Rau, N Kondylidis, J Kamps The Twenty-Ninth Text REtrieval Conference Notebook (TREC 2020). National …, 2020 | 2 | 2020 |
| Recall Aspects of Transformers for Text Ranking D Rau, J Kamps Gaithersburg, MDNational Institute for Standards and Technology (NIST), 0 | 2* | |
| BERGEN: A Benchmarking Library for Retrieval-Augmented Generation D Rau, H Déjean, N Chirkova, T Formal, S Wang, V Nikoulina, ... arXiv preprint arXiv:2407.01102, 2024 | 1 | 2024 |
| Retrieval-augmented generation in multilingual settings N Chirkova, D Rau, H Déjean, T Formal, S Clinchant, V Nikoulina arXiv preprint arXiv:2407.01463, 2024 | 1 | 2024 |
| Query Generation Using Large Language Models: A Reproducibility Study of Unsupervised Passage Reranking D Rau, J Kamps European Conference on Information Retrieval, 226-239, 2024 | 1 | 2024 |
| University of amsterdam at trec 2021: Deep learning track J Kamps, D Rau TREC, 2021 | 1 | 2021 |
| University of Amsterdam at the CLEF 2023 SimpleText Track. R Hutter, J Sutmuller, M Adib, D Rau, J Kamps CLEF (Working Notes), 3007-3016, 2023 | | 2023 |
| Efficient Document Representations for Neural Text Ranking. D Rau, J Kamps TREC, 2022 | | 2022 |
| Sparsely-gated mixture-of-experts PyTorch Implementation D Rau https://github. com/davidmrau/mixture-of-experts, 2019 | | 2019 |
| Environment-related differences of Deep Q-learning and Double Deep Q-learning S Rajamanickam, D Rau, D Ulmer, C Winkler | | |
Vikram AlvaMax Planck Institute for BiologyVerified email at tuebingen.mpg.de
