default search action
Navid Rekabsaz
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [j4]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) - [c53]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: 11743-11776 - [c52]Carolin Holtermann, Markus Frohmann, Navid Rekabsaz, Anne Lauscher:
What the Weight?! A Unified Framework for Zero-Shot Knowledge Composition. EACL (Findings) 2024: 1138-1157 - [c51]Shahed Masoudian, Cornelia Volaucnik, Markus Schedl, Navid Rekabsaz:
Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters. EACL (1) 2024: 2434-2453 - [c50]Linda Ratz, Markus Schedl, Simone Kopeinik, Navid Rekabsaz:
Measuring Bias in Search Results Through Retrieval List Comparison. ECIR (5) 2024: 20-34 - [c49]Shahed Masoudian, Markus Frohmann, Navid Rekabsaz, Markus Schedl:
Unlabeled Debiasing in Downstream Tasks via Class-wise Low Variance Regularization. EMNLP 2024: 10932-10938 - [i30]Carolin Holtermann, Markus Frohmann, Navid Rekabsaz, Anne Lauscher:
What the Weight?! A Unified Framework for Zero-Shot Knowledge Composition. CoRR abs/2401.12756 (2024) - [i29]Shahed Masoudian, Cornelia Volaucnik, Markus Schedl, Navid Rekabsaz:
Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters. CoRR abs/2401.16457 (2024) - [i28]Shahed Masoudian, Markus Frohmann, Navid Rekabsaz, Markus Schedl:
Unlabeled Debiasing in Downstream Tasks via Class-wise Low Variance Regularization. CoRR abs/2409.19541 (2024) - 2023
- [j3]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) - [c48]Lukas Hauzenberger, Shahed Masoudian
Modular and On-demand Bias Mitigation with Attribute-Removal Subnetworks. ACL (Findings) 2023: 6192-6214 - [c47]Simone Kopeinik
Show me a "Male Nurse"! How Gender Bias is Reflected in the Query Formulation of Search Engine Users. CHI 2023: 137:1-137:15 - [c46]Klara Krieg
Grep-BiasIR: A Dataset for Investigating Gender Representation Bias in Information Retrieval Results. CHIIR 2023: 444-448 - [c45]Deepak Kumar
Parameter-efficient Modularised Bias Mitigation via AdapterFusion. EACL 2023: 2730-2743 - [c44]George Zerveas, Navid Rekabsaz, Carsten Eickhoff:
Enhancing the Ranking Context of Dense Retrieval through Reciprocal Nearest Neighbors. EMNLP 2023: 10779-10803 - [c43]Shahed Masoudian
Domain Information Control at Inference Time for Acoustic Scene Classification. EUSIPCO 2023: 181-185 - [c42]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 - [c41]Nicolò Tamagnone, Selim Fekih, Ximena Contla, Nayid Orozco, Navid Rekabsaz:
Leveraging Domain Knowledge for Inclusive and Bias-aware Humanitarian Response Entry Classification. IJCAI 2023: 6219-6227 - [c40]Oleg Lesota
Computational Versus Perceived Popularity Miscalibration in Recommender Systems. SIGIR 2023: 1889-1893 - [i27]Christopher Wimmer, Navid Rekabsaz:
Leveraging Vision-Language Models for Granular Market Change Prediction. CoRR abs/2301.10166 (2023) - [i26]Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, Navid Rekabsaz:
Parameter-efficient Modularised Bias Mitigation via AdapterFusion. CoRR abs/2302.06321 (2023) - [i25]George Zerveas, Navid Rekabsaz, Carsten Eickhoff:
Enhancing the Ranking Context of Dense Retrieval Methods through Reciprocal Nearest Neighbors. CoRR abs/2305.15720 (2023) - [i24]Nicolò Tamagnone, Selim Fekih, Ximena Contla, Nayid Orozco, Navid Rekabsaz:
Leveraging Domain Knowledge for Inclusive and Bias-aware Humanitarian Response Entry Classification. CoRR abs/2305.16756 (2023) - [i23]Shahed Masoudian, Khaled Koutini, Markus Schedl, Gerhard Widmer, Navid Rekabsaz:
Domain Information Control at Inference Time for Acoustic Scene Classification. CoRR abs/2306.08010 (2023) - [i22]Markus Frohmann, Carolin Holtermann, Shahed Masoudian, Anne Lauscher, Navid Rekabsaz:
ScaLearn: Simple and Highly Parameter-Efficient Task Transfer by Learning to Scale. CoRR abs/2310.01217 (2023) - 2022
- [c39]Klara Krieg, Emilia Parada-Cabaleiro, Markus Schedl, Navid Rekabsaz:
Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements? BIAS 2022: 104-116 - [c38]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: 337-341 - [c37]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: 4379-4389 - [c36]George Zerveas, Navid Rekabsaz, Daniel Cohen, Carsten Eickhoff:
CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking. EMNLP 2022: 10626-10644 - [c35]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: 291-297 - [c34]Benjamin Minixhofer, Fabian Paischer, Navid Rekabsaz:
WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models. NAACL-HLT 2022: 3992-4006 - [c33]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 - [c32]Alessandro B. Melchiorre
ProtoMF: Prototype-based Matrix Factorization for Effective and Explainable Recommendations. RecSys 2022: 246-256 - [c31]Christian Ganhör
Unlearning Protected User Attributes in Recommendations with Adversarial Training. SIGIR 2022: 2142-2147 - [c30]George Zerveas, Navid Rekabsaz, Daniel Cohen, Carsten Eickhoff:
Mitigating Bias in Search Results Through Contextual Document Reranking and Neutrality Regularization. SIGIR 2022: 2532-2538 - [c29]Daniel Cohen, Kevin Du, Bhaskar Mitra, Laura Mercurio, Navid Rekabsaz, Carsten Eickhoff:
Inconsistent Ranking Assumptions in Medical Search and Their Downstream Consequences. SIGIR 2022: 2572-2577 - [c28]Markus Schedl, Navid Rekabsaz, Elisabeth Lex, Tessa Grosz, Elisabeth Greif:
Multiperspective and Multidisciplinary Treatment of Fairness in Recommender Systems Research. UMAP (Adjunct Publication) 2022: 90-94 - [i21]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 abs/2201.07754 (2022) - [i20]Klara Krieg, Emilia Parada-Cabaleiro, Markus Schedl, Navid Rekabsaz:
Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements? CoRR abs/2203.01731 (2022) - [i19]Lukas Hauzenberger, Navid Rekabsaz:
Parameter Efficient Diff Pruning for Bias Mitigation. CoRR abs/2205.15171 (2022) - [i18]Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl:
Unlearning Protected User Attributes in Recommendations with Adversarial Training. CoRR abs/2206.04500 (2022) - [i17]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 abs/2210.04573 (2022) - 2021
- [j2]Alessandro B. Melchiorre
Investigating gender fairness of recommendation algorithms in the music domain. Inf. Process. Manag. 58(5): 102666 (2021) - [c27]Jenny Paola Yela-Bello, Ewan Oglethorpe, Navid Rekabsaz:
MultiHumES: Multilingual Humanitarian Dataset for Extractive Summarization. EACL 2021: 1713-1717 - [c26]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: 185-195 - [c25]Navid Rekabsaz, Robert West, James Henderson, Allan Hanbury:
Measuring Societal Biases from Text Corpora with Smoothed First-Order Co-occurrence. ICWSM 2021: 549-560 - [c24]Oleg Lesota, Alessandro B. Melchiorre
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected? RecSys 2021: 601-606 - [c23]Navid Rekabsaz, Simone Kopeinik, Markus Schedl:
Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation of BERT Rankers. SIGIR 2021: 306-316 - [c22]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: 654-664 - [c21]Navid Rekabsaz, Oleg Lesota, Markus Schedl, Jon Brassey, Carsten Eickhoff:
TripClick: The Log Files of a Large Health Web Search Engine. SIGIR 2021: 2507-2513 - [i16]Navid Rekabsaz, Oleg Lesota, Markus Schedl, Jon Brassey, Carsten Eickhoff:
TripClick: The Log Files of a Large Health Web Search Engine. CoRR abs/2103.07901 (2021) - [i15]Navid Rekabsaz, Simone Kopeinik, Markus Schedl:
Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation for BERT Rankers. CoRR abs/2104.13640 (2021) - [i14]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 abs/2105.04651 (2021) - [i13]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 abs/2106.13618 (2021) - [i12]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 abs/2108.06973 (2021) - [i11]Benjamin Minixhofer, Fabian Paischer, Navid Rekabsaz:
WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models. CoRR abs/2112.06598 (2021) - [i10]George Zerveas, Navid Rekabsaz, Daniel Cohen, Carsten Eickhoff:
CODER: An efficient framework for improving retrieval through COntextualized Document Embedding Reranking. CoRR abs/2112.08766 (2021) - 2020
- [c20]Markus Zlabinger, Sebastian Hofstätter, Navid Rekabsaz, Allan Hanbury:
DSR: A Collection for the Evaluation of Graded Disease-Symptom Relations. ECIR (2) 2020: 433-440 - [c19]Navid Rekabsaz, Markus Schedl:
Do Neural Ranking Models Intensify Gender Bias? SIGIR 2020: 2065-2068 - [i9]Markus Zlabinger, Sebastian Hofstätter, Navid Rekabsaz, Allan Hanbury:
DSR: A Collection for the Evaluation of Graded Disease-Symptom Relations. CoRR abs/2001.05357 (2020) - [i8]Navid Rekabsaz, Markus Schedl:
Do Neural Ranking Models Intensify Gender Bias? CoRR abs/2005.00372 (2020)
2010 – 2019
- 2019
- [c18]Markus Zlabinger, Navid Rekabsaz, Stefan Zlabinger, Allan Hanbury:
Efficient Answer-Annotation for Frequent Questions. CLEF 2019: 126-137 - [c17]Sebastian Hofstätter, Navid Rekabsaz, Mihai Lupu, Carsten Eickhoff, Allan Hanbury:
Enriching Word Embeddings for Patent Retrieval with Global Context. ECIR (1) 2019: 810-818 - [c16]Sebastian Hofstätter, Navid Rekabsaz, Carsten Eickhoff, Allan Hanbury:
On the Effect of Low-Frequency Terms on Neural-IR Models. SIGIR 2019: 1137-1140 - [i7]Sebastian Hofstätter, Navid Rekabsaz, Carsten Eickhoff, Allan Hanbury:
On the Effect of Low-Frequency Terms on Neural-IR Models. CoRR abs/1904.12683 (2019) - [i6]Navid Rekabsaz, Nikolaos Pappas, James Henderson, Banriskhem K. Khonglah, Srikanth R. Madikeri:
Regularization Advantages of Multilingual Neural Language Models for Low Resource Domains. CoRR abs/1906.01496 (2019) - 2018
- [i5]Navid Rekabsaz, Allan Hanbury:
An Unbiased Approach to Quantification of Gender Inclination using Interpretable Word Representations. CoRR abs/1812.10424 (2018) - 2017
- [j1]Navid Rekabsaz, Ralf Bierig
Toward Optimized Multimodal Concept Indexing. Trans. Comput. Collect. Intell. 26: 144-161 (2017) - [c15]Navid Rekabsaz, Mihai Lupu, Artem Baklanov
Volatility Prediction using Financial Disclosures Sentiments with Word Embedding-based IR Models. ACL (1) 2017: 1712-1721 - [c14]João R. M. Palotti, Navid Rekabsaz:
Exploring Understandability Features to Personalize Consumer Health Search. TUW at CLEF 2017 eHealth. CLEF (Working Notes) 2017 - [c13]Navid Rekabsaz, Mihai Lupu, Allan Hanbury:
Exploration of a Threshold for Similarity Based on Uncertainty in Word Embedding. ECIR 2017: 396-409 - [c12]Navid Rekabsaz, Mihai Lupu, Allan Hanbury, Hamed Zamani:
Word Embedding Causes Topic Shifting; Exploit Global Context! SIGIR 2017: 1105-1108 - [i4]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 abs/1702.01978 (2017) - [i3]Navid Rekabsaz, Bhaskar Mitra, Mihai Lupu, Allan Hanbury:
Toward Incorporation of Relevant Documents in word2vec. CoRR abs/1707.06598 (2017) - [i2]Navid Rekabsaz, Mihai Lupu, Allan Hanbury, Andrés Duque:
Addressing Cross-Lingual Word Sense Disambiguation on Low-Density Languages: Application to Persian. CoRR abs/1711.06196 (2017) - 2016
- [c11]Navid Rekabsaz, Mihai Lupu, Allan Hanbury, Guido Zuccon
Generalizing Translation Models in the Probabilistic Relevance Framework. CIKM 2016: 711-720 - [c10]Navid Rekabsaz, Serwah Sabetghadam, Mihai Lupu, Linda Andersson, Allan Hanbury:
Standard Test Collection for English-Persian Cross-Lingual Word Sense Disambiguation. LREC 2016 - [c9]Navid Rekabsaz:
Enhancing Information Retrieval with Adapted Word Embedding. SIGIR 2016: 1169 - [i1]Navid Rekabsaz, Mihai Lupu, Allan Hanbury:
Uncertainty in Neural Network Word Embedding: Exploration of Threshold for Similarity. CoRR abs/1606.06086 (2016) - 2015
- [c8]Navid Rekabsaz, Ralf Bierig, Bogdan Ionescu, Allan Hanbury, Mihai Lupu:
On the use of statistical semantics for metadata-based social image retrieval. CBMI 2015: 1-4 - [c7]Navid Rekabsaz, Ralf Bierig
Toward Optimized Multimodal Concept Indexing. International KEYSTONE Conference 2015: 141-152 - [c6]Soheil Qanbari, Navid Rekabsaz, Schahram Dustdar
Open Government Data as a Service (GoDaaS): Big Data Platform for Mobile App Developers. FiCloud 2015: 398-403 - [c5]Serwah Sabetghadam, João R. M. Palotti, Navid Rekabsaz, Mihai Lupu, Allan Hanbury:
TUW @ MediaEval 2015 Retrieving Diverse Social Images Task. MediaEval 2015 - 2014
- [c4]Navid Rekabsaz, Mihai Lupu:
A Real-World Framework for Translator as Expert Retrieval. CLEF 2014: 141-152 - [c3]Alexandru-Lucian Gînsca, Adrian Popescu, Navid Rekabsaz:
CEA LIST's Participation at the MediaEval 2014 Retrieving Diverse Social Images Task. MediaEval 2014 - [c2]João R. M. Palotti, Navid Rekabsaz, Mihai Lupu, Allan Hanbury:
TUW @ Retrieving Diverse Social Images Task 2014. MediaEval 2014 - [c1]João R. M. Palotti, Navid Rekabsaz, Linda Andersson, Allan Hanbury:
TUW @ TREC Clinical Decision Support Track. TREC 2014
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-15 19:32 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: