{"list":"other","total":62,"rows":[{"id":"1908.09635","title":"A Survey on Bias and Fairness in Machine Learning","created":"2019-08-23","cited_by_count":1917},{"id":"1403.6652","title":"DeepWalk: Online Learning of Social Representations","created":"2014-03-26","cited_by_count":1547},{"id":"1806.01261","title":"Relational inductive biases, deep learning, and graph networks","created":"2018-06-04","cited_by_count":1360},{"id":"1708.05031","title":"Neural Collaborative Filtering","created":"2017-08-16","cited_by_count":1111},{"id":"1703.06856","title":"Counterfactual Fairness","created":"2017-03-20","cited_by_count":804},{"id":"1503.03578","title":"LINE: Large-scale Information Network Embedding","created":"2015-03-12","cited_by_count":582},{"id":"1602.05352","title":"Recommendations as Treatments: Debiasing Learning and Evaluation","created":"2016-02-17","cited_by_count":248},{"id":"2010.03240","title":"Bias and Debias in Recommender System: A Survey and Future Directions","created":"2020-10-07","cited_by_count":240},{"id":"1511.05897","title":"Censoring Representations with an Adversary","created":"2015-11-18","cited_by_count":192},{"id":"1608.04468","title":"Unbiased Learning-to-Rank with Biased Feedback","created":"2016-08-16","cited_by_count":157},{"id":"1705.10378","title":"Fair Inference On Outcomes","created":"2017-05-29","cited_by_count":144},{"id":"1905.01989","title":"Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search","created":"2019-04-30","cited_by_count":138},{"id":"1903.00780","title":"Fairness in Recommendation Ranking through Pairwise Comparisons","created":"2019-03-02","cited_by_count":127},{"id":"1905.10674","title":"Compositional Fairness Constraints for Graph Embeddings","created":"2019-05-25","cited_by_count":126},{"id":"1805.01788","title":"Equity of Attention: Amortizing Individual Fairness in Rankings","created":"2018-05-04","cited_by_count":124},{"id":"1706.06368","title":"FA*IR: A Fair Top-k Ranking Algorithm","created":"2017-06-20","cited_by_count":113},{"id":"1906.11668","title":"Artificial Intelligence: the global landscape of ethics guidelines","created":"2019-06-24","cited_by_count":107},{"id":"1708.05024","title":"Fast Matrix Factorization for Online Recommendation with Implicit Feedback","created":"2017-08-16","cited_by_count":101},{"id":"1705.08804","title":"Beyond Parity: Fairness Objectives for Collaborative Filtering","created":"2017-05-24","cited_by_count":93},{"id":"2007.13019","title":"Feedback Loop and Bias Amplification in Recommender Systems","created":"2020-07-25","cited_by_count":90},{"id":"1901.07555","title":"Managing Popularity Bias in Recommender Systems with Personalized Re-ranking","created":"2019-01-22","cited_by_count":82},{"id":"1610.08559","title":"Measuring Fairness in Ranked Outputs","created":"2016-10-26","cited_by_count":81},{"id":"1510.07025","title":"Modeling User Exposure in Recommendation","created":"2015-10-23","cited_by_count":69},{"id":"2005.14713","title":"Controlling Fairness and Bias in Dynamic Learning-to-Rank","created":"2020-05-29","cited_by_count":68},{"id":"2105.04170","title":"AutoDebias: Learning to Debias for Recommendation","created":"2021-05-10","cited_by_count":68},{"id":"1902.10730","title":"Degenerate Feedback Loops in Recommender Systems","created":"2019-02-27","cited_by_count":67},{"id":"1804.05938","title":"Unbiased Learning to Rank with Unbiased Propensity Estimation","created":"2018-04-16","cited_by_count":61},{"id":"1907.09013","title":"Conscientious Classification: A Data Scientist's Guide to Discrimination-Aware Classification","created":"2019-07-21","cited_by_count":55},{"id":"1712.09752","title":"Designing Fair Ranking Schemes","created":"2017-12-28","cited_by_count":40},{"id":"2103.06364","title":"User-centered Evaluation of Popularity Bias in Recommender Systems","created":"2021-03-10","cited_by_count":38},{"id":"2002.06961","title":"Citation Recommendation: Approaches and Datasets","created":"2020-02-17","cited_by_count":36},{"id":"2001.11358","title":"Correcting for Selection Bias in Learning-to-rank Systems","created":"2020-01-29","cited_by_count":35},{"id":"1812.05161","title":"Estimating Position Bias without Intrusive Interventions","created":"2018-12-12","cited_by_count":32},{"id":"2005.10545","title":"ESAM: Discriminative Domain Adaptation with Non-Displayed Items to Improve Long-Tail Performance","created":"2020-05-21","cited_by_count":30},{"id":"1910.01444","title":"Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback","created":"2019-09-08","cited_by_count":28},{"id":"2006.15772","title":"Multi-sided Exposure Bias in Recommendation","created":"2020-06-29","cited_by_count":23},{"id":"1707.00574","title":"How algorithmic popularity bias hinders or promotes quality","created":"2017-07-03","cited_by_count":20},{"id":"1804.04212","title":"Word2Vec applied to Recommendation: Hyperparameters Matter","created":"2018-04-11","cited_by_count":20},{"id":"2005.00962","title":"Gender Gap in Natural Language Processing Research: Disparities in Authorship and Citations","created":"2020-05-03","cited_by_count":17},{"id":"2106.07041","title":"Correcting Exposure Bias for Link Recommendation","created":"2021-06-13","cited_by_count":17},{"id":"1803.01901","title":"On Discrimination Discovery and Removal in Ranked Data using Causal Graph","created":"2018-03-05","cited_by_count":16},{"id":"1906.11964","title":"OpenCitations, an infrastructure organization for open scholarship","created":"2019-06-27","cited_by_count":16},{"id":"2005.11938","title":"Cascade Model-based Propensity Estimation for Counterfactual Learning to Rank","created":"2020-05-25","cited_by_count":15},{"id":"1811.01802","title":"Intervention Harvesting for Context-Dependent Examination-Bias Estimation","created":"2018-11-05","cited_by_count":14},{"id":"1907.04103","title":"Historical comparison of gender inequality in scientific careers across countries and disciplines","created":"2019-07-09","cited_by_count":14},{"id":"1802.06565","title":"A Study of Position Bias in Digital Library Recommender Systems","created":"2018-02-19","cited_by_count":13},{"id":"2004.14329","title":"Google Scholar, Microsoft Academic, Scopus, Dimensions, Web of Science, and OpenCitations' COCI: a multidisciplinary comparison of coverage via citations","created":"2020-04-29","cited_by_count":11},{"id":"1610.08984","title":"Quantitative Evaluation of Gender Bias in Astronomical Publications from Citation Counts","created":"2016-10-27","cited_by_count":10},{"id":"2005.08480","title":"Non-Clicks Mean Irrelevant? Propensity Ratio Scoring As a Correction","created":"2020-05-18","cited_by_count":10},{"id":"1905.06221","title":"Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets","created":"2019-05-15","cited_by_count":8},{"id":"1303.7274","title":"Reputation and Impact in Academic Careers","created":"2013-03-29","cited_by_count":7},{"id":"2010.12864","title":"On Transferability of Bias Mitigation Effects in Language Model Fine-Tuning","created":"2020-10-24","cited_by_count":5},{"id":"1906.07883","title":"Gender trends in computer science authorship","created":"2019-06-19","cited_by_count":3},{"id":"2111.05097","title":"Cross-Lingual Citations in English Papers: A Large-Scale Analysis of Prevalence, Usage, and Impact","created":"2021-11-07","cited_by_count":2},{"id":"2111.05564","title":"Understanding and Mitigating Multi-Sided Exposure Bias in Recommender Systems","created":"2021-11-10","cited_by_count":2},{"id":"1301.3885","title":"Collaborative Filtering by Personality Diagnosis: A Hybrid Memory- and Model-Based Approach","created":"2013-01-16","cited_by_count":1},{"id":"1303.7149","title":"Usage-based vs. Citation-based Methods for Recommending Scholarly Research Articles","created":"2013-03-28","cited_by_count":1},{"id":"1503.05702","title":"The Open Access Advantage Considering Citation, Article Usage and Social Media Attention","created":"2015-03-19","cited_by_count":1},{"id":"1511.05266","title":"Semi-supervised Collaborative Ranking with Push at Top","created":"2015-11-17","cited_by_count":1},{"id":"1803.09905","title":"Conformity in Scientific Networks","created":"2018-03-27","cited_by_count":1},{"id":"1809.05818","title":"Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm","created":"2018-09-16","cited_by_count":1},{"id":"1902.09089","title":"The Matthew Effect in Computation Contests: High Difficulty May Lead to 51% Dominance","created":"2019-02-25","cited_by_count":1}],"next_cursor":null}