Theo dõi
Navid Rekabsaz
Navid Rekabsaz
Thomson Reuters AI Labs
Email được xác minh tại thomsonreuters.com - Trang chủ
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Năm
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
1552021
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
962017
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
862021
Do Neural Ranking Models Intensify Gender Bias?
N Rekabsaz, M Schedl
Proceedings of the 43rd International ACM SIGIR conference on research and …, 2020
842020
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
802022
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
762021
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
592022
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
592017
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
56*2022
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
502021
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
412019
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
392022
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
352023
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
352017
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
342016
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
332021
Protomf: Prototype-based matrix factorization for effective and explainable recommendations
AB Melchiorre, N Rekabsaz, C Ganhör, M Schedl
Proceedings of the 16th ACM Conference on Recommender Systems, 246-256, 2022
302022
Parameter-efficient modularised bias mitigation via AdapterFusion
D Kumar, O Lesota, G Zerveas, D Cohen, C Eickhoff, M Schedl, ...
arXiv preprint arXiv:2302.06321, 2023
262023
Modular and on-demand bias mitigation with attribute-removal subnetworks
L Hauzenberger, S Masoudian, D Kumar, M Schedl, N Rekabsaz
arXiv preprint arXiv:2205.15171, 2022
23*2022
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
232021
Hệ thống không thể thực hiện thao tác ngay bây giờ. Hãy thử lại sau.
Bài viết 1–20