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2020 – today
- 2022
[c29]Klara Krieg, Emilia Parada-Cabaleiro, Markus Schedl, Navid Rekabsaz:
Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements? BIAS 2022: 104-116- [c28]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 - [i20]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) - [i19]Klara Krieg, Emilia Parada-Cabaleiro, Markus Schedl, Navid Rekabsaz:
Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements? CoRR abs/2203.01731 (2022) - [i18]Lukas Hauzenberger, Navid Rekabsaz:
Parameter Efficient Diff Pruning for Bias Mitigation. CoRR abs/2205.15171 (2022) - [i17]Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl:
Unlearning Protected User Attributes in Recommendations with Adversarial Training. CoRR abs/2206.04500 (2022) - 2021
- [j2]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): 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, 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: 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, Mihai Lupu, Allan Hanbury:
Toward Optimized Multimodal Concept Indexing. Trans. Comput. Collect. Intell. 26: 144-161 (2017) - [c15]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: 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, Mihai Lupu, Allan Hanbury:
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
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last updated on 2022-06-30 22:49 CEST by the dblp team
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