Publications
2024
Unlabeled Debiasing in Downstream Tasks via Class-wise Low Variance Regularization
Shahed Masoudian, Markus Frohmann, Navid Rekabsaz, Markus Schedl
In proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters
Shahed Masoudian, Cornelia Volaucnik, Markus Schedl, Navid Rekabsaz
In proceedings of the 18th Annual Meeting of the European chapter of the Association for Computational Linguistics (EACL), March 2024.
2023
Parameter-efficient Modularised Bias Mitigation via AdapterFusion
Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, Navid Rekabsaz
In proceedings of 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL), May 2023.
Show me a "Male Nurse"! How Gender Bias is Reflected in the Query Formulation of Search Engine Users
Simone Kopeinik, Martina Mara, Linda Ratz, Klara Krieg, Markus Schedl, Navid Rekabsaz
In proceedings of the ACM Conference on Human Factors in Computing Systems (CHI), 2023.
Computational Versus Perceived Popularity Miscalibration in Recommender Systems
Oleg Lesota, Gustavo Escobedo, Yashar Deldjoo, Bruce Ferwerda, Simone Kopeinik, Elisabeth Lex, Navid Rekabsaz and Markus Schedl
In proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023
Natural Language Processing for humanitarian action: opportunities, challenges, and the path towards humanitarian NLP
Roberta Rocca, Nicolò Tamagnone, Selim Fekih, Ximena Contla, Navid Rekabsaz
Frontiers in Big Data. 2023
Fairness of Recommender Systems in the Recruitment Domain: An Analysis from Technical and Legal Perspectives
Deepak Kumar, Tessa Grosz, Navid Rekabsaz, Elisabeth Greif, Markus Schedl
Frontiers in Big Data. 2023
Grep-BiasIR: A Dataset for Investigating Gender Representation-Bias in Information Retrieval Results
Klara Krieg, Emilia Parada-Cabaleiro, Gertraud Medicus, Oleg Lesota, Markus Schedl, Navid Rekabsaz
In proceedings of the 2023 ACM SIGIR Conference On Human Information Interaction And Retrieval (CHIIR), March 2023.
Domain Information Control at Inference Time for Acoustic Scene Classification
Shahed Masoudian, Khaled Koutini, Markus Schedl, Gerhard Widmer, Navid Rekabsaz
In proceedings of the 31st European Signal Processing Conference (EUSIPCO), 2023
Leveraging Vision-Language Models for Granular Market Change Prediction
Christopher Wimmer, Navid Rekabsaz
In proceedings of the Workshop On Multimodal AI For Financial Forecasting at Association for the Advancement of Artificial Intelligence (Muffin@AAAI), 2023
Identifying Words in Job Advertisements Responsible for Gender Bias in Candidate Ranking Systems via Counterfactual Learning
Deepak Kumar, Tessa Grosz, Elisabeth Greif, Navid Rekabsaz, Markus Schedl
In proceedings of the Workshop On Recommender Systems for Human Resources (RecSys in HR), 2023
2022
WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models
Benjamin Minixhofer, Fabian Paischer, Navid Rekabsaz
In proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), July 2022.
HumSet: Dataset of Multilingual Information Extraction and Classification for Humanitarian Crises Response
Selim Fekih, Nicolo' Tamagnone, Benjamin Minixhofer, Ranjan Shrestha, Ximena Contla, Ewan Oglethorpe and Navid Rekabsaz
In Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP), December 2022.
Mitigating bias in search results through set-based document reranking and neutrality regularization
George Zerveas, Navid Rekabsaz, Daniel Cohen, Carsten Eickhoff
In proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), July 2022.
Inconsistent Ranking Assumptions in Medical Search and Their Downstream Consequences
Daniel Cohen, Kevin Du, Bhaskar Mitra, Laura Mercurio, Navid Rekabsaz, Carsten Eickhoff
In proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), July 2022.
Traces of Globalization in Online Music Consumption Patterns and Results of Recommendation Algorithms
Oleg Lesota, Emilia Parada-Cabaleiro, Elisabeth Lex, Navid Rekabsaz, Stefan Brandl, Markus Schedl
In proceedings of the 23rd International Society for Music Information Retrieval Conference (ISMIR), December 2022.
**Best Student Paper**
LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis
Markus Schedl, Stefan Brandl, Oleg Lesota, Emilia Parada-Cabaleiro, David Penz, Navid Rekabsaz
In proceedings of ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR), 2022
Multiperspective and Multidisciplinary Treatment of Fairness in Recommender Systems Research
Markus Schedl, Navid Rekabsaz, Elisabeth Lex, Tessa Grosz, Elisabeth Greif
In Adjunct proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (UMAP '22 Adjunct), 2022
Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements?
Klara Krieg, Emilia Parada-Cabaleiro, Markus Schedl, Navid Rekabsaz
In proceedings of the European Conference on Information Retrieval - Algorithmic Bias in Search and Recommendation Workshop (BIAS@ECIR), April 2022
Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization
Oleg Lesota, Stefan Brandl, Matthias Wenzel, Alessandro Benedetto Melchiorre, Elisabeth Lex, Navid Rekabsaz, Markus Schedl
In proceedings of the 16th ACM Recommender Systems Conference - Multi-Objective Recommender Systems Workshop (MORS@RecSys), Sep 2022.
2021
Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation of BERT Rankers
Navid Rekabsaz, Simone Kopeinik, Markus Schedl
In proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), July 2021.
TripClick: The Log Files of a Large Health Web Search Engine
Navid Rekabsaz, Oleg Lesota, Markus Schedl, Jon Brassey, Carsten Eickhoff
In proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), July 2021.
Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models
Daniel Cohen, Bhaskar Mitra, Oleg Lesota, Navid Rekabsaz, Carsten Eickhoff
In proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), July 2021.
MultiHumES: Multilingual Humanitarian Dataset for Extractive Summarization
Jenny Paola Yela Bello, Ewan Oglethorpe, Navid Rekabsaz
In proceedings of the 16th Conference of the European Chapter of Association for Computational Linguistics (EACL), April 2021
Analyzing item popularity bias of music recommender systems: Are different genders equally affected?
Lesota O., Melchiorre A., Rekabsaz N., Brandl S., Kowald D., Lex E., Schedl M.
In proceedings of the 15th ACM Conference on Recommender Systems (RecSys), 2021
2020
2019
Enriching Word Embeddings for Patent Retrieval with Global Context
Sebastian Hofstätter, Navid Rekabsaz, Mihai Lupu, Carsten Eickhoff and Allan Hanbury
In proceedings of the European Conference on Information Retrieval (ECIR), 2019
Efficient Answer-Annotation for Frequent Questions
Markus Zlabinger, Navid Rekabsaz, Stefan Zlabinger and Allan Hanbury
In proceedings of the Conference and Labs of the Evaluation Forum (CLEF), 2019
Regularization Advantages of Multilingual Neural Language Models for Low Resource Domains
Navid Rekabsaz, Nikolaos Pappas, James Henderson, Banriskhem K. Khonglah, Srikanth Madikeri
2018
Word Representation for Text Analysis and Search: Document Retrieval, Sentiment Analysis, and Cross Lingual Word Sense Disambiguation
Navid Rekabsaz
PhD Thesis. Doktor der Technischen Wissenschaften
2017
Volatility Prediction using Financial Disclosures Sentiments with Word Embedding-based IR Models
Navid Rekabsaz, Mihai Lupu, Artem Baklanov, Allan Hanbury, Alexander Duer, Linda Anderson
In proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2017
Word Embedding Causes Topic Shifting; Exploit Global Context!
Navid Rekabsaz, Mihai Lupu, Hamed Zamani, Allan Hanbury
In proceedings of the ACM Conference on Research and Development in Information Retrieval (SIGIR), 2017
Exploration of a Threshold for Similarity based on Uncertainty in Word Embedding
Navid Rekabsaz, Mihai Lupu, Allan Hanbury
In proceedings of the European Conference on Information Retrieval (ECIR), 2017
Toward Incorporation of Relevant Documents in word2vec
Navid Rekabsaz, Bhaskar Mitra, Mihai Lupu, Allan Hanbury
Neu-IR Workshop at the ACM Conference on Research and Development in Information Retrieval (NeuIR-SIGIR), 2017
2016
Generalizing Translation Models in the Probabilistic Relevance Framework
Navid Rekabsaz, Mihai Lupu, Allan Hanbury, Guido Zuccon
In proceedings of the ACM International Conference on Information and Knowledge Management (CIKM), 2016
Standard Test Collection for English-Persian Cross-Lingual Word Sense Disambiguation
Navid Rekabsaz, Serwah Sabetghadam, Mihai Lupu, Linda Andersson, Allan Hanbury
In proceedings of the Language Resources and Evaluation Conference (LREC) 2016
Toward Optimized Multimodal Concept Indexing
Navid Rekabsaz, Ralf Bierig, Mihai Lupu, Allan Hanbury
Journal of Transactions on Computational Collective Intelligence (TCCI) 2016
Uncertainty in Neural Network Word Embedding: Exploration of Threshold for Similarity
Navid Rekabsaz, Mihai Lupu, Allan Hanbury
Neu-IR Workshop at the ACM Conference on Research and Development in Information Retrieval (NeuIR-SIGIR) 2016
2015
Toward Optimized Multimodal Concept Indexing
Navid Rekabsaz, Ralf Bierig, Mihai Lupu, Allan Hanbury
In proceedings of the 1st International KEYSTONE Conference (IKC) 2015
Open Government data as a Service (GoDaaS): Big data Platform for Mobile App Developers
Soheil Qanbari, Navid Rekabsaz, Schahram Dustdar
In proceedings of the IEEE International Conference on Open and Big data (IEEE OBD) 2015
On the Use of Statistical Semantics for Metadata-based Social Image Retrieval
Navid Rekabsaz, Ralf Bierig, Bogdan Ionescu, Allan Hanbury, Mihai Lupu
In proceedings of the 13th International Workshop on Content-Based Multimedia Indexing (CBMI) 2015
TUW @ MediaEval 2015 Retrieving Diverse Social Images Task
João R. M. Palotti, Serwah Sabetghadam, Navid Rekabsaz, Mihai Lupu, Allan Hanbury
In proceedings of the MediaEval Workshop 2015
2014
A Real-World Framework for Translator as Expert Retrieval
Navid Rekabsaz, Mihai Lupu
In proceedings of the of the 5th international Conference and Labs of the Evaluation Forum (CLEF) 2014
TUW @ TREC Clinical Decision Support Track
João R. M. Palotti, Navid Rekabsaz, Linda Anderson, Allan Hanbury
In proceedings of the Twenty-Third Text REtrieval Conference (TREC) 2014
TUW @ Retrieving Diverse Social Images Task
João R. M. Palotti, Navid Rekabsaz, Mihai Lupu, Allan Hanbury
In proceedings of the MediaEval Workshop, 2014
CEA LIST’s Participation at the MediaEval 2014 Retrieving Diverse Social Images Task
Alexandru Lucian Gînscă, Adrian Popescu, Navid Rekabsaz
In proceedings of the MediaEval Workshop, 2014