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Navid Rekabsaz
Navid Rekabsaz
Thomson Reuters AI Labs
Verified email at thomsonreuters.com - Homepage
Title
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Cited by
Year
Investigating gender fairness of recommendation algorithms in the music domain
AB Melchiorre, N Rekabsaz, E Parada-Cabaleiro, S Brandl, O Lesota, ...
Information Processing & Management 58 (5), 102666, 2021
1212021
Volatility prediction using financial disclosures sentiments with word embedding-based IR models
N Rekabsaz, M Lupu, A Baklanov, A Hanbury, A Dür, L Anderson
Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017
892017
Do Neural Ranking Models Intensify Gender Bias?
N Rekabsaz, M Schedl
Proceedings of the 43rd International ACM SIGIR conference on research and …, 2020
682020
Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation of BERT Rankers
N Rekabsaz, S Kopeinik, M Schedl
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
672021
Analyzing item popularity bias of music recommender systems: are different genders equally affected?
O Lesota, A Melchiorre, N Rekabsaz, S Brandl, D Kowald, E Lex, ...
Proceedings of the 15th ACM conference on recommender systems, 601-606, 2021
572021
Exploration of a threshold for similarity based on uncertainty in word embedding
N Rekabsaz, M Lupu, A Hanbury
Advances in Information Retrieval: 39th European Conference on IR Research …, 2017
532017
WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models
B Minixhofer, F Paischer, N Rekabsaz
Proceedings of the 2022 Conference of the North American Chapter of the …, 2022
512022
Tripclick: the log files of a large health web search engine
N Rekabsaz, O Lesota, M Schedl, J Brassey, C Eickhoff
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
402021
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
402019
LFM-2b: A dataset of enriched music listening events for recommender systems research and fairness analysis
M Schedl, S Brandl, O Lesota, E Parada-Cabaleiro, D Penz, N Rekabsaz
Proceedings of the 2022 Conference on Human Information Interaction and …, 2022
392022
Word embedding causes topic shifting; exploit global context!
N Rekabsaz, M Lupu, A Hanbury, H Zamani
Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017
342017
Mitigating bias in search results through contextual document reranking and neutrality regularization
G Zerveas, N Rekabsaz, D Cohen, C Eickhoff
Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022
332022
Generalizing translation models in the probabilistic relevance framework
N Rekabsaz, M Lupu, A Hanbury, G Zuccon
Proceedings of the 25th ACM international on conference on information and …, 2016
332016
Unlearning protected user attributes in recommendations with adversarial training
C Ganhör, D Penz, N Rekabsaz, O Lesota, M Schedl
Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022
32*2022
Grep-biasir: A dataset for investigating gender representation bias in information retrieval results
K Krieg, E Parada-Cabaleiro, G Medicus, O Lesota, M Schedl, ...
Proceedings of the 2023 Conference on Human Information Interaction and …, 2023
302023
Not all relevance scores are equal: Efficient uncertainty and calibration modeling for deep retrieval models
D Cohen, B Mitra, O Lesota, N Rekabsaz, C Eickhoff
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
302021
Measuring Societal Biases from Text Corpora with Smoothed First-Order Co-occurrence
N Rekabsaz, R West, J Henderson, A Hanbury
Proceedings of the International AAAI Conference on Web and Social Media, 2021
202021
Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements?
K Krieg, E Parada-Cabaleiro, M Schedl, N Rekabsaz
International Workshop on Algorithmic Bias in Search and Recommendation, 104-116, 2022
182022
A modern perspective on query likelihood with deep generative retrieval models
O Lesota, N Rekabsaz, D Cohen, KA Grasserbauer, C Eickhoff, M Schedl
Proceedings of the 2021 ACM SIGIR International Conference on Theory of …, 2021
182021
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
182019
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