Navid Rekabsaz

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 76

Top Topics

Word Sense Disambiguation

Nearest Neighbor

Top Venues

Publications

Linda Ratz, Markus Schedl, Simone Kopeinik, Navid Rekabsaz
Measuring Bias in Search Results Through Retrieval List Comparison. ECIR (5) (2024)
Carolin Holtermann, Markus Frohmann, Navid Rekabsaz, Anne Lauscher
What the Weight?! A Unified Framework for Zero-Shot Knowledge Composition. EACL (Findings) (2024)
Shahed Masoudian, Cornelia Volaucnik, Markus Schedl, Navid Rekabsaz
Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters. EACL (1) (2024)
Deepak Kumar, Tessa Grosz, Navid Rekabsaz, Elisabeth Greif, Markus Schedl
Fairness of recommender systems in the recruitment domain: an analysis from technical and legal perspectives. Frontiers Big Data 6 (2024)
Carolin Holtermann, Markus Frohmann, Navid Rekabsaz, Anne Lauscher
What the Weight?! A Unified Framework for Zero-Shot Knowledge Composition. CoRR (2024)
Markus Frohmann, Carolin Holtermann, Shahed Masoudian, Anne Lauscher, Navid Rekabsaz
ScaLearn: Simple and Highly Parameter-Efficient Task Transfer by Learning to Scale. ACL (Findings) (2024)
Lukas Hauzenberger, Shahed Masoudian, Deepak Kumar, Markus Schedl, Navid Rekabsaz
Modular and On-demand Bias Mitigation with Attribute-Removal Subnetworks. ACL (Findings) (2023)
Klara Krieg, Emilia Parada-Cabaleiro, Gertraud Medicus, Oleg Lesota, Markus Schedl, Navid Rekabsaz
Grep-BiasIR: A Dataset for Investigating Gender Representation Bias in Information Retrieval Results. CHIIR (2023)
Simone Kopeinik, Martina Mara, Linda Ratz, Klara Krieg, Markus Schedl, Navid Rekabsaz
Show me a "Male Nurse"! How Gender Bias is Reflected in the Query Formulation of Search Engine Users. CHI (2023)
Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, Navid Rekabsaz
Parameter-efficient Modularised Bias Mitigation via AdapterFusion. EACL (2023)
Nicolò Tamagnone, Selim Fekih, Ximena Contla, Nayid Orozco, Navid Rekabsaz
Leveraging Domain Knowledge for Inclusive and Bias-aware Humanitarian Response Entry Classification. CoRR (2023)
George Zerveas, Navid Rekabsaz, Carsten Eickhoff
Enhancing the Ranking Context of Dense Retrieval through Reciprocal Nearest Neighbors. EMNLP (2023)
Shahed Masoudian, Khaled Koutini, Markus Schedl, Gerhard Widmer, Navid Rekabsaz
Domain Information Control at Inference Time for Acoustic Scene Classification. EUSIPCO (2023)
George Zerveas, Navid Rekabsaz, Carsten Eickhoff
Enhancing the Ranking Context of Dense Retrieval Methods through Reciprocal Nearest Neighbors. CoRR (2023)
Shahed Masoudian, Khaled Koutini, Markus Schedl, Gerhard Widmer, Navid Rekabsaz
Domain Information Control at Inference Time for Acoustic Scene Classification. CoRR (2023)
Deepak Kumar, Tessa Grosz, Elisabeth Greif, Navid Rekabsaz, Markus Schedl
Identifying Words in Job Advertisements Responsible for Gender Bias in Candidate Ranking Systems via Counterfactual Learning. HR@RecSys (2023)
Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, Navid Rekabsaz
Parameter-efficient Modularised Bias Mitigation via AdapterFusion. CoRR (2023)
Oleg Lesota, Gustavo Escobedo, Yashar Deldjoo, Bruce Ferwerda, Simone Kopeinik, Elisabeth Lex, Navid Rekabsaz, Markus Schedl
Computational Versus Perceived Popularity Miscalibration in Recommender Systems. SIGIR (2023)
Roberta Rocca, Nicolò Tamagnone, Selim Fekih, Ximena Contla, Navid Rekabsaz
Natural language processing for humanitarian action: Opportunities, challenges, and the path toward humanitarian NLP. Frontiers Big Data 6 (2023)
Christopher Wimmer, Navid Rekabsaz
Leveraging Vision-Language Models for Granular Market Change Prediction. CoRR (2023)
Nicolò Tamagnone, Selim Fekih, Ximena Contla, Nayid Orozco, Navid Rekabsaz
Leveraging Domain Knowledge for Inclusive and Bias-aware Humanitarian Response Entry Classification. IJCAI (2023)
Markus Frohmann, Carolin Holtermann, Shahed Masoudian, Anne Lauscher, Navid Rekabsaz
ScaLearn: Simple and Highly Parameter-Efficient Task Transfer by Learning to Scale. CoRR (2023)
George Zerveas, Navid Rekabsaz, Daniel Cohen, Carsten Eickhoff
CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking. EMNLP (2022)
Benjamin Minixhofer, Fabian Paischer, Navid Rekabsaz
WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models. NAACL-HLT (2022)
Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl
Unlearning Protected User Attributes in Recommendations with Adversarial Training. SIGIR (2022)
Oleg Lesota, Emilia Parada-Cabaleiro, Stefan Brandl, Elisabeth Lex, Navid Rekabsaz, Markus Schedl
Traces of Globalization in Online Music Consumption Patterns and Results of Recommendation Algorithms. ISMIR (2022)
Selim Fekih, Nicolò Tamagnone, Benjamin Minixhofer, Ranjan Shrestha, Ximena Contla, Ewan Oglethorpe, Navid Rekabsaz
HumSet: Dataset of Multilingual Information Extraction and Classification for Humanitarian Crisis Response. CoRR (2022)
Alessandro B. Melchiorre, Navid Rekabsaz, Christian Ganhör, Markus Schedl
ProtoMF: Prototype-based Matrix Factorization for Effective and Explainable Recommendations. RecSys (2022)
Oleg Lesota, Stefan Brandl, Matthias Wenzel, Alessandro B. Melchiorre, Elisabeth Lex, Navid Rekabsaz, Markus Schedl
Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization. MORS@RecSys (2022)
Markus Schedl, Stefan Brandl, Oleg Lesota, Emilia Parada-Cabaleiro, David Penz, Navid Rekabsaz
LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis. CHIIR (2022)
Klara Krieg, Emilia Parada-Cabaleiro, Markus Schedl, Navid Rekabsaz
Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements? BIAS (2022)
Lukas Hauzenberger, Navid Rekabsaz
Parameter Efficient Diff Pruning for Bias Mitigation. CoRR (2022)
Selim Fekih, Nicolò Tamagnone, Benjamin Minixhofer, Ranjan Shrestha, Ximena Contla, Ewan Oglethorpe, Navid Rekabsaz
HumSet: Dataset of Multilingual Information Extraction and Classification for Humanitarian Crises Response. EMNLP (Findings) (2022)
Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl
Unlearning Protected User Attributes in Recommendations with Adversarial Training. CoRR (2022)
George Zerveas, Navid Rekabsaz, Daniel Cohen, Carsten Eickhoff
Mitigating Bias in Search Results Through Contextual Document Reranking and Neutrality Regularization. SIGIR (2022)
Klara Krieg, Emilia Parada-Cabaleiro, Gertraud Medicus, Oleg Lesota, Markus Schedl, Navid Rekabsaz
Grep-BiasIR: A Dataset for Investigating Gender Representation-Bias in Information Retrieval Results. CoRR (2022)
Klara Krieg, Emilia Parada-Cabaleiro, Markus Schedl, Navid Rekabsaz
Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements? CoRR (2022)
Daniel Cohen, Kevin Du, Bhaskar Mitra, Laura Mercurio, Navid Rekabsaz, Carsten Eickhoff
Inconsistent Ranking Assumptions in Medical Search and Their Downstream Consequences. SIGIR (2022)
Markus Schedl, Navid Rekabsaz, Elisabeth Lex, Tessa Grosz, Elisabeth Greif
Multiperspective and Multidisciplinary Treatment of Fairness in Recommender Systems Research. UMAP (Adjunct Publication) (2022)
Navid Rekabsaz, Simone Kopeinik, Markus Schedl
Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation for BERT Rankers. CoRR (2021)
Navid Rekabsaz, Robert West, James Henderson, Allan Hanbury
Measuring Societal Biases from Text Corpora with Smoothed First-Order Co-occurrence. ICWSM (2021)
Benjamin Minixhofer, Fabian Paischer, Navid Rekabsaz
WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models. CoRR (2021)
Navid Rekabsaz, Oleg Lesota, Markus Schedl, Jon Brassey, Carsten Eickhoff
TripClick: The Log Files of a Large Health Web Search Engine. SIGIR (2021)
Alessandro B. Melchiorre, Navid Rekabsaz, Emilia Parada-Cabaleiro, Stefan Brandl, Oleg Lesota, Markus Schedl
Investigating gender fairness of recommendation algorithms in the music domain. Inf. Process. Manag. 58 (5) (2021)
Jenny Paola Yela-Bello, Ewan Oglethorpe, Navid Rekabsaz
MultiHumES: Multilingual Humanitarian Dataset for Extractive Summarization. EACL (2021)
Oleg Lesota, Alessandro B. Melchiorre, Navid Rekabsaz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected? CoRR (2021)
George Zerveas, Navid Rekabsaz, Daniel Cohen, Carsten Eickhoff
CODER: An efficient framework for improving retrieval through COntextualized Document Embedding Reranking. CoRR (2021)
Oleg Lesota, Navid Rekabsaz, Daniel Cohen, Klaus Antonius Grasserbauer, Carsten Eickhoff, Markus Schedl
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models. CoRR (2021)
Daniel Cohen, Bhaskar Mitra, Oleg Lesota, Navid Rekabsaz, Carsten Eickhoff
Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models. CoRR (2021)
Oleg Lesota, Navid Rekabsaz, Daniel Cohen, Klaus Antonius Grasserbauer, Carsten Eickhoff, Markus Schedl
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models. ICTIR (2021)
Navid Rekabsaz, Oleg Lesota, Markus Schedl, Jon Brassey, Carsten Eickhoff
TripClick: The Log Files of a Large Health Web Search Engine. CoRR (2021)
Daniel Cohen, Bhaskar Mitra, Oleg Lesota, Navid Rekabsaz, Carsten Eickhoff
Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models. SIGIR (2021)
Navid Rekabsaz, Simone Kopeinik, Markus Schedl
Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation of BERT Rankers. SIGIR (2021)
Oleg Lesota, Alessandro B. Melchiorre, Navid Rekabsaz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected? RecSys (2021)
Markus Zlabinger, Sebastian Hofstätter, Navid Rekabsaz, Allan Hanbury
DSR: A Collection for the Evaluation of Graded Disease-Symptom Relations. CoRR (2020)
Markus Zlabinger, Sebastian Hofstätter, Navid Rekabsaz, Allan Hanbury
DSR: A Collection for the Evaluation of Graded Disease-Symptom Relations. ECIR (2) (2020)
Navid Rekabsaz, Markus Schedl
Do Neural Ranking Models Intensify Gender Bias? SIGIR (2020)
Navid Rekabsaz, Markus Schedl
Do Neural Ranking Models Intensify Gender Bias? CoRR (2020)
Markus Zlabinger, Navid Rekabsaz, Stefan Zlabinger, Allan Hanbury
Efficient Answer-Annotation for Frequent Questions. CLEF (2019)
Sebastian Hofstätter, Navid Rekabsaz, Carsten Eickhoff, Allan Hanbury
On the Effect of Low-Frequency Terms on Neural-IR Models. CoRR (2019)
Navid Rekabsaz, Nikolaos Pappas, James Henderson, Banriskhem K. Khonglah, Srikanth R. Madikeri
Regularization Advantages of Multilingual Neural Language Models for Low Resource Domains. CoRR (2019)
Sebastian Hofstätter, Navid Rekabsaz, Carsten Eickhoff, Allan Hanbury
On the Effect of Low-Frequency Terms on Neural-IR Models. SIGIR (2019)
Sebastian Hofstätter, Navid Rekabsaz, Mihai Lupu, Carsten Eickhoff, Allan Hanbury
Enriching Word Embeddings for Patent Retrieval with Global Context. ECIR (1) (2019)
Navid Rekabsaz, Allan Hanbury
An Unbiased Approach to Quantification of Gender Inclination using Interpretable Word Representations. CoRR (2018)
Navid Rekabsaz, Mihai Lupu, Artem Baklanov, Alexander Dür, Linda Andersson, Allan Hanbury
Volatility Prediction using Financial Disclosures Sentiments with Word Embedding-based IR Models. ACL (1) (2017)
Navid Rekabsaz, Mihai Lupu, Allan Hanbury, Andrés Duque
Addressing Cross-Lingual Word Sense Disambiguation on Low-Density Languages: Application to Persian. CoRR (2017)
Navid Rekabsaz, Mihai Lupu, Allan Hanbury
Exploration of a Threshold for Similarity Based on Uncertainty in Word Embedding. ECIR (2017)
Navid Rekabsaz, Mihai Lupu, Allan Hanbury, Hamed Zamani
Word Embedding Causes Topic Shifting; Exploit Global Context! SIGIR (2017)
Navid Rekabsaz, Ralf Bierig, Mihai Lupu, Allan Hanbury
Toward Optimized Multimodal Concept Indexing. Trans. Comput. Collect. Intell. 26 (2017)
Navid Rekabsaz, Bhaskar Mitra, Mihai Lupu, Allan Hanbury
Toward Incorporation of Relevant Documents in word2vec. CoRR (2017)
João R. M. Palotti, Navid Rekabsaz
Exploring Understandability Features to Personalize Consumer Health Search. TUW at CLEF 2017 eHealth. CLEF (Working Notes) (2017)
Navid Rekabsaz, Mihai Lupu, Artem Baklanov, Allan Hanbury, Alexander Dür, Linda Andersson
Volatility Prediction using Financial Disclosures Sentiments with Word Embedding-based IR Models. CoRR (2017)
Navid Rekabsaz
Enhancing Information Retrieval with Adapted Word Embedding. SIGIR (2016)
Navid Rekabsaz, Mihai Lupu, Allan Hanbury
Uncertainty in Neural Network Word Embedding: Exploration of Threshold for Similarity. CoRR (2016)
Navid Rekabsaz, Serwah Sabetghadam, Mihai Lupu, Linda Andersson, Allan Hanbury
Standard Test Collection for English-Persian Cross-Lingual Word Sense Disambiguation. LREC (2016)
Navid Rekabsaz, Mihai Lupu, Allan Hanbury, Guido Zuccon
Generalizing Translation Models in the Probabilistic Relevance Framework. CIKM (2016)
Navid Rekabsaz, Ralf Bierig, Bogdan Ionescu, Allan Hanbury, Mihai Lupu
On the use of statistical semantics for metadata-based social image retrieval. CBMI (2015)
Navid Rekabsaz, Ralf Bierig, Mihai Lupu, Allan Hanbury
Toward Optimized Multimodal Concept Indexing. International KEYSTONE Conference (2015)
Soheil Qanbari, Navid Rekabsaz, Schahram Dustdar
Open Government Data as a Service (GoDaaS): Big Data Platform for Mobile App Developers. FiCloud (2015)
Serwah Sabetghadam, João R. M. Palotti, Navid Rekabsaz, Mihai Lupu, Allan Hanbury
TUW @ MediaEval 2015 Retrieving Diverse Social Images Task. MediaEval (2015)
Alexandru-Lucian Gînsca, Adrian Popescu, Navid Rekabsaz
CEA LIST's Participation at the MediaEval 2014 Retrieving Diverse Social Images Task. MediaEval (2014)
Navid Rekabsaz, Mihai Lupu
A Real-World Framework for Translator as Expert Retrieval. CLEF (2014)
João R. M. Palotti, Navid Rekabsaz, Linda Andersson, Allan Hanbury
TUW @ TREC Clinical Decision Support Track. TREC (2014)
João R. M. Palotti, Navid Rekabsaz, Mihai Lupu, Allan Hanbury
TUW @ Retrieving Diverse Social Images Task 2014. MediaEval (2014)