{"list":"other","total":60,"rows":[{"id":"1610.07524","title":"Fair prediction with disparate impact: A study of bias in recidivism prediction instruments","created":"2016-10-24","cited_by_count":672},{"id":"1609.05807","title":"Inherent Trade-Offs in the Fair Determination of Risk Scores","created":"2016-09-19","cited_by_count":586},{"id":"2002.06673","title":"Performative Prediction","created":"2020-02-16","cited_by_count":327},{"id":"1912.05511","title":"Measurement and Fairness","created":"2019-12-11","cited_by_count":308},{"id":"1506.06980","title":"Strategic Classification","created":"2015-06-23","cited_by_count":257},{"id":"1803.04383","title":"Delayed Impact of Fair Machine Learning","created":"2018-03-12","cited_by_count":184},{"id":"1710.11214","title":"How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility","created":"2017-10-30","cited_by_count":120},{"id":"1909.04847","title":"RecSim: A Configurable Simulation Platform for Recommender Systems","created":"2019-09-11","cited_by_count":94},{"id":"2007.13019","title":"Feedback Loop and Bias Amplification in Recommender Systems","created":"2020-07-25","cited_by_count":90},{"id":"1807.05307","title":"How Do Classifiers Induce Agents To Invest Effort Strategically?","created":"2018-07-13","cited_by_count":83},{"id":"2402.06627","title":"Feedback Loops With Language Models Drive In-Context Reward Hacking","created":"2024-02-09","cited_by_count":77},{"id":"1902.10730","title":"Degenerate Feedback Loops in Recommender Systems","created":"2019-02-27","cited_by_count":67},{"id":"1808.00720","title":"RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising","created":"2018-08-02","cited_by_count":65},{"id":"1702.07274","title":"Rotting Bandits","created":"2017-02-23","cited_by_count":57},{"id":"1502.04147","title":"Bayesian Incentive-Compatible Bandit Exploration","created":"2015-02-13","cited_by_count":53},{"id":"1912.04883","title":"Roles for Computing in Social Change","created":"2019-12-10","cited_by_count":49},{"id":"2106.12705","title":"Alternative Microfoundations for Strategic Classification","created":"2021-06-24","cited_by_count":47},{"id":"2009.09153","title":"Hidden Incentives for Auto-Induced Distributional Shift","created":"2020-09-19","cited_by_count":43},{"id":"2204.01266","title":"CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System","created":"2022-04-04","cited_by_count":38},{"id":"2206.13102","title":"Modeling Content Creator Incentives on Algorithm-Curated Platforms","created":"2022-06-27","cited_by_count":35},{"id":"1806.00955","title":"A Game-Theoretic Approach to Recommendation Systems with Strategic Content Providers","created":"2018-06-04","cited_by_count":33},{"id":"2206.13489","title":"Supply-Side Equilibria in Recommender Systems","created":"2022-06-27","cited_by_count":33},{"id":"2008.00104","title":"Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach","created":"2020-07-31","cited_by_count":32},{"id":"1910.14354","title":"Recovering Bandits","created":"2019-10-31","cited_by_count":29},{"id":"2202.11776","title":"The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization","created":"2022-02-23","cited_by_count":29},{"id":"2204.11966","title":"Estimating and Penalizing Induced Preference Shifts in Recommender Systems","created":"2022-04-25","cited_by_count":29},{"id":"2302.01971","title":"How Bad is Top-$K$ Recommendation under Competing Content Creators?","created":"2023-02-03","cited_by_count":27},{"id":"1910.02757","title":"Stochastic Bandits with Delay-Dependent Payoffs","created":"2019-10-07","cited_by_count":25},{"id":"2011.07931","title":"Do Offline Metrics Predict Online Performance in Recommender Systems?","created":"2020-11-07","cited_by_count":25},{"id":"2205.13026","title":"Preference Dynamics Under Personalized Recommendations","created":"2022-05-25","cited_by_count":25},{"id":"2109.04083","title":"User Tampering in Reinforcement Learning Recommender Systems","created":"2021-09-09","cited_by_count":23},{"id":"2008.12623","title":"From Optimizing Engagement to Measuring Value","created":"2020-08-21","cited_by_count":21},{"id":"2103.08057","title":"RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems","created":"2021-03-14","cited_by_count":21},{"id":"2004.03865","title":"Manipulation-Proof Machine Learning","created":"2020-04-08","cited_by_count":20},{"id":"2011.06741","title":"Rebounding Bandits for Modeling Satiation Effects","created":"2020-11-13","cited_by_count":19},{"id":"2204.10817","title":"Reward Reports for Reinforcement Learning","created":"2022-04-22","cited_by_count":18},{"id":"2308.04399","title":"Fine-Tuning Games: Bargaining and Adaptation for General-Purpose Models","created":"2023-08-08","cited_by_count":17},{"id":"2306.14670","title":"Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition","created":"2023-06-26","cited_by_count":14},{"id":"2305.06055","title":"A Classification of Feedback Loops and Their Relation to Biases in Automated Decision-Making Systems","created":"2023-05-10","cited_by_count":13},{"id":"2401.09804","title":"Clickbait vs. Quality: How Engagement-Based Optimization Shapes the Content Landscape in Online Platforms","created":"2024-01-18","cited_by_count":13},{"id":"2202.05716","title":"Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systems","created":"2022-02-11","cited_by_count":12},{"id":"2302.04336","title":"Performative Recommendation: Diversifying Content via Strategic Incentives","created":"2023-02-08","cited_by_count":12},{"id":"2203.13423","title":"Modeling Attrition in Recommender Systems with Departing Bandits","created":"2022-03-25","cited_by_count":11},{"id":"2203.10666","title":"YouTube, The Great Radicalizer? Auditing and Mitigating Ideological Biases in YouTube Recommendations","created":"2022-03-20","cited_by_count":10},{"id":"2306.07893","title":"Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?","created":"2023-06-13","cited_by_count":10},{"id":"2210.07773","title":"Diversified Recommendations for Agents with Adaptive Preferences","created":"2022-09-20","cited_by_count":9},{"id":"2110.11819","title":"A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits","created":"2021-10-22","cited_by_count":8},{"id":"2208.01534","title":"Towards Psychologically-Grounded Dynamic Preference Models","created":"2022-08-01","cited_by_count":8},{"id":"2302.01377","title":"Learning with Exposure Constraints in Recommendation Systems","created":"2023-02-02","cited_by_count":8},{"id":"2302.06559","title":"Recommending to Strategic Users","created":"2023-02-13","cited_by_count":8},{"id":"2309.06375","title":"Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models","created":"2023-09-08","cited_by_count":7},{"id":"2306.07479","title":"Incentivizing High-Quality Content in Online Recommender Systems","created":"2023-06-13","cited_by_count":6},{"id":"2311.15647","title":"Bandits Meet Mechanism Design to Combat Clickbait in Online Recommendation","created":"2023-11-27","cited_by_count":6},{"id":"2302.06014","title":"Online Recommendations for Agents with Discounted Adaptive Preferences","created":"2023-02-12","cited_by_count":5},{"id":"2311.16586","title":"SARDINE: A Simulator for Automated Recommendation in Dynamic and Interactive Environments","created":"2023-11-28","cited_by_count":5},{"id":"2401.00313","title":"Matching of Users and Creators in Two-Sided Markets with Departures","created":"2023-12-30","cited_by_count":5},{"id":"2211.13585","title":"Learning to Suggest Breaks: Sustainable Optimization of Long-Term User Engagement","created":"2022-11-24","cited_by_count":3},{"id":"2306.00338","title":"Last Switch Dependent Bandits with Monotone Payoff Functions","created":"2023-06-01","cited_by_count":3},{"id":"2312.17666","title":"User Strategization and Trustworthy Algorithms","created":"2023-12-29","cited_by_count":3},{"id":"2304.09088","title":"A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits","created":"2023-04-16","cited_by_count":1}],"next_cursor":null}