Maria De-Arteaga

59 papers A* 5B 1C 1Journal 42Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Should You Use LLMs to Simulate Opinions? Quality Checks for Early-Stage Deliberation. AAAI Terrence Neumann, Maria De-Arteaga, Sina Fazelpour
2025	J	`jnl`	Bias-Aware Mislabeling Detection via Decoupled Confident Learning. CoRR Yunyi Li, Maria De-Arteaga, Maytal Saar-Tsechansky
2025	J	`jnl`	Finding Pareto trade-offs in fair and accurate detection of toxic speech. Inf. Res. Soumyajit Gupta, Venelin Kovatchev, Anubrata Das, Maria De-Arteaga, Matthew Lease
2025	J	`jnl`	Leveraging Expert Consistency to Improve Algorithmic Decision Support. Manag. Sci. Maria De-Arteaga, Vincent Jeanselme, Artur Dubrawski, Alexandra Chouldechova
2025	J	`jnl`	More of the Same: Persistent Representational Harms Under Increased Representation. CoRR Jennifer Mickel, Maria De-Arteaga, Leqi Liu, Kevin Tian
2025	—	`conf`	Perils of Label Indeterminacy: A Case Study on Prediction of Neurological Recovery After Cardiac Arrest. FAccT Jakob Schoeffer, Maria De-Arteaga, Jonathan Elmer
2025	J	`jnl`	Perils of Label Indeterminacy: A Case Study on Prediction of Neurological Recovery After Cardiac Arrest. CoRR Jakob Schoeffer, Maria De-Arteaga, Jonathan Elmer
2025	J	`jnl`	Should you use LLMs to simulate opinions? Quality checks for early-stage deliberation. CoRR Terrence Neumann, Maria De-Arteaga, Sina Fazelpour
2024	—	`conf`	A Critical Survey on Fairness Benefits of Explainable AI. FAccT Luca Deck, Jakob Schoeffer, Maria De-Arteaga, Niklas Kühl
2024	J	`jnl`	Diverse, but Divisive: LLMs Can Exaggerate Gender Differences in Opinion Related to Harms of Misinformation. CoRR Terrence Neumann, Sooyong Lee, Maria De-Arteaga, Sina Fazelpour, Matthew Lease
2024	A*	`conf`	Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making. CHI Jakob Schoeffer, Maria De-Arteaga, Niklas Kühl
2024	J	`jnl`	Fairly Accurate: Optimizing Accuracy Parity in Fair Target-Group Detection. CoRR Soumyajit Gupta, Venelin Kovatchev, Maria De-Arteaga, Matthew Lease
2024	J	`jnl`	Fighting Bias with Bias: A Machine Learning Approach to Assess Human Bias. CoRR Wanxue Dong, Maria De-Arteaga, Maytal Saar-Tsechansky
2023	J	`jnl`	A Critical Survey on Fairness Benefits of XAI. CoRR Luca Deck, Jakob Schoeffer, Maria De-Arteaga, Niklas Kühl
2023	—	`conf`	Human-Centered Responsible Artificial Intelligence: Current & Future Trends. CHI Extended Abstracts Mohammad Tahaei, Marios Constantinides, Daniele Quercia, Sean Kennedy, Michael J. Muller, Simone Stumpf, Q. Vera Liao, Ricardo Baeza-Yates, Lora Aroyo, Jess Holbrook, Ewa Luger, Michael Madaio, Ilana Golbin Blumenfeld, Maria De-Arteaga, Jessica Vitak, Alexandra Olteanu
2023	J	`jnl`	Human-Centered Responsible Artificial Intelligence: Current & Future Trends. CoRR Mohammad Tahaei, Marios Constantinides, Daniele Quercia, Sean Kennedy, Michael J. Muller, Simone Stumpf, Q. Vera Liao, Ricardo Baeza-Yates, Lora Aroyo, Jess Holbrook, Ewa Luger, Michael Madaio, Ilana Golbin Blumenfeld, Maria De-Arteaga, Jessica Vitak, Alexandra Olteanu
2023	J	`jnl`	Learning Complementary Policies for Human-AI Teams. CoRR Ruijiang Gao, Maytal Saar-Tsechansky, Maria De-Arteaga, Ligong Han, Wei Sun, Min Kyung Lee, Matthew Lease
2023	J	`jnl`	Mitigating Label Bias via Decoupled Confident Learning. CoRR Yunyi Li, Maria De-Arteaga, Maytal Saar-Tsechansky
2023	A*	`conf`	Same Same, But Different: Conditional Multi-Task Learning for Demographic-Specific Toxicity Detection. WWW Soumyajit Gupta, Sooyong Lee, Maria De-Arteaga, Matthew Lease
2023	J	`jnl`	Same Same, But Different: Conditional Multi-Task Learning for Demographic-Specific Toxicity Detection. CoRR Soumyajit Gupta, Sooyong Lee, Maria De-Arteaga, Matthew Lease
2023	J	`jnl`	Social norm bias: residual harms of fairness-aware algorithms. Data Min. Knowl. Discov. Myra Cheng, Maria De-Arteaga, Lester Mackey, Adam Tauman Kalai
2023	J	`jnl`	Toward Supporting Perceptual Complementarity in Human-AI Collaboration via Reflection on Unobservables. Proc. ACM Hum. Comput. Interact. Kenneth Holstein, Maria De-Arteaga, Lakshmi Tumati, Yanghuidi Cheng
2022	J	`jnl`	Algorithmic Fairness in Business Analytics: Directions for Research and Practice. CoRR Maria De-Arteaga, Stefan Feuerriegel, Maytal Saar-Tsechansky
2022	J	`jnl`	Diversity in sociotechnical machine learning systems. Big Data Soc. Sina Fazelpour, Maria De-Arteaga
2022	J	`jnl`	Doubting AI Predictions: Influence-Driven Second Opinion Recommendation. CoRR Maria De-Arteaga, Alexandra Chouldechova, Artur Dubrawski
2022	—	`conf`	Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness. ML4H@NeurIPS Vincent Jeanselme, Maria De-Arteaga, Zhe Zhang, Jessica K. Barrett, Brian D. M. Tom
2022	J	`jnl`	Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness. CoRR Vincent Jeanselme, Maria De-Arteaga, Zhe Zhang, Jessica K. Barrett, Brian D. M. Tom
2022	—	`conf`	Justice in Misinformation Detection Systems: An Analysis of Algorithms, Stakeholders, and Potential Harms. FAccT Terrence Neumann, Maria De-Arteaga, Sina Fazelpour
2022	J	`jnl`	Justice in Misinformation Detection Systems: An Analysis of Algorithms, Stakeholders, and Potential Harms. CoRR Terrence Neumann, Maria De-Arteaga, Sina Fazelpour
2022	J	`jnl`	More Data Can Lead Us Astray: Active Data Acquisition in the Presence of Label Bias. CoRR Yunyi Li, Maria De-Arteaga, Maytal Saar-Tsechansky
2022	J	`jnl`	On Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making. CoRR Jakob Schoeffer, Maria De-Arteaga, Niklas Kühl
2022	J	`jnl`	On the Relationship Between Explanations, Fairness Perceptions, and Decisions. CoRR Jakob Schoeffer, Maria De-Arteaga, Niklas Kühl
2022	J	`jnl`	Toward Supporting Perceptual Complementarity in Human-AI Collaboration via Reflection on Unobservables. CoRR Kenneth Holstein, Maria De-Arteaga, Lakshmi Tumati, Yanghuidi Cheng
2022	B	`conf`	When More Data Lead Us Astray: Active Data Acquisition in the Presence of Label Bias. HCOMP Yunyi Li, Maria De-Arteaga, Maytal Saar-Tsechansky
2021	J	`jnl`	Diversity in Sociotechnical Machine Learning Systems. CoRR Sina Fazelpour, Maria De-Arteaga
2021	A*	`conf`	Human-AI Collaboration with Bandit Feedback. IJCAI Ruijiang Gao, Maytal Saar-Tsechansky, Maria De-Arteaga, Ligong Han, Min Kyung Lee, Matthew Lease
2021	J	`jnl`	Human-AI Collaboration with Bandit Feedback. CoRR Ruijiang Gao, Maytal Saar-Tsechansky, Maria De-Arteaga, Ligong Han, Min Kyung Lee, Matthew Lease
2021	J	`jnl`	Leveraging Expert Consistency to Improve Algorithmic Decision Support. CoRR Maria De-Arteaga, Artur Dubrawski, Alexandra Chouldechova
2021	J	`jnl`	Social Norm Bias: Residual Harms of Fairness-Aware Algorithms. CoRR Myra Cheng, Maria De-Arteaga, Lester Mackey, Adam Tauman Kalai
2021	—	`conf`	The effect of differential victim crime reporting on predictive policing systems. FAccT Nil-Jana Akpinar, Maria De-Arteaga, Alexandra Chouldechova
2021	J	`jnl`	The effect of differential victim crime reporting on predictive policing systems. CoRR Nil-Jana Akpinar, Maria De-Arteaga, Alexandra Chouldechova
2020	A*	`conf`	A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores. CHI Maria De-Arteaga, Riccardo Fogliato, Alexandra Chouldechova
2020	J	`jnl`	A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores. CoRR Maria De-Arteaga, Riccardo Fogliato, Alexandra Chouldechova
2020	J	`jnl`	Proceedings of NeurIPS 2019 Workshop on Machine Learning for the Developing World: Challenges and Risks of ML4D. CoRR Maria De-Arteaga, Tejumade Afonja, Amanda Coston
2019	—	`conf`	Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. FAT Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
2019	J	`jnl`	Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. CoRR Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
2019	J	`jnl`	Killings of social leaders in the Colombian post-conflict: Data analysis for investigative journalism. CoRR Maria De-Arteaga, Benedikt Boecking
2019	C	`conf`	What are the Biases in My Word Embedding? AIES Nathaniel Swinger, Maria De-Arteaga, Neil Thomas Heffernan IV, Mark D. M. Leiserson, Adam Tauman Kalai
2019	—	`conf`	What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. NAACL-HLT (1) Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Kalai
2019	J	`jnl`	What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. CoRR Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai
2018	J	`jnl`	Learning under selective labels in the presence of expert consistency. CoRR Maria De-Arteaga, Artur Dubrawski, Alexandra Chouldechova
2018	J	`jnl`	Machine Learning for the Developing World. ACM Trans. Manag. Inf. Syst. Maria De-Arteaga, William Herlands, Daniel B. Neill, Artur Dubrawski
2018	J	`jnl`	Proceedings of NeurIPS 2018 Workshop on Machine Learning for the Developing World: Achieving Sustainable Impact. CoRR Maria De-Arteaga, Amanda Coston, William Herlands
2018	J	`jnl`	What are the biases in my word embedding? CoRR Nathaniel Swinger, Maria De-Arteaga, Neil Thomas Heffernan IV, Mark D. M. Leiserson, Adam Tauman Kalai
2015	J	`jnl`	Analyzing Medical Image Search Behavior: Semantics and Prediction of Query Results. J. Digit. Imaging Maria De-Arteaga, Ivan Eggel, Charles E. Kahn Jr., Henning Müller
2015	J	`jnl`	Canonical Autocorrelation Analysis. CoRR Maria De-Arteaga, Artur Dubrawski, Peter Huggins
2015	J	`jnl`	Comparing image search behaviour in the ARRS GoldMiner search engine and a clinical PACS/RIS. J. Biomed. Informatics Maria De-Arteaga, Ivan Eggel, Bao H. Do, Daniel L. Rubin, Charles E. Kahn Jr., Henning Müller
2014	—	`conf`	MindLab-UNAL: Comparing Metamap and T-mapper for Medical Concept Extraction in SemEval 2014 Task 7. SemEval@COLING Alejandro Riveros, Maria De-Arteaga, Fabio A. González, Sergio Jiménez, Henning Müller
2013	—	`conf`	Author Profiling Using Corpus Statistics, Lexicons and Stylistic Features Notebook for PAN at CLEF-2013. CLEF (Working Notes) Maria De-Arteaga, Sergio Jiménez, George Dueñas, Sergio Mancera, Julia Baquero