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David Rau
David Rau
Verified email at uva.nl
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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
20812018
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
162019
How Different are Pre-trained Transformers for Text Ranking?
D Rau, J Kamps
European Conference on Information Retrieval, 207-214, 2022
142022
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
122022
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
122019
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
72021
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
52022
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
22020
Recall Aspects of Transformers for Text Ranking
D Rau, J Kamps
Gaithersburg, MDNational Institute for Standards and Technology (NIST), 0
2*
University of amsterdam at trec 2021: Deep learning track
J Kamps, D Rau
TREC, 2021
12021
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
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
2024
Revisiting Bag of Words Document Representations for Efficient Ranking with Transformers
D Rau, M Dehghani, J Kamps
ACM Transactions on Information Systems, 2024
2024
University of Amsterdam at the CLEF 2023 SimpleText Track
R Hutter, J Sutmuller, M Adib, D Rau, J Kamps
2023
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
Efficient Document Representations for Neural Text Ranking
D Rau, J Kamps
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Articles 1–17