Joachim Baumann

33 papers A* 4Journal 16Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	GoogleTrendArchive: A Year-Long Archive of Real-Time Web Search Trends Worldwide. CoRR Aleksandra Urman, Anikó Hannák, Joachim Baumann
2025	J	`jnl`	AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons. CoRR Shaona Ghosh, Heather Frase, Adina Williams, Sarah Luger, Paul Röttger, Fazl Barez, Sean McGregor, Kenneth Fricklas, Mala Kumar, Quentin Feuillade-Montixi, Kurt D. Bollacker, Felix Friedrich, Ryan Tsang, Bertie Vidgen, Alicia Parrish, Chris Knotz, Eleonora Presani, Jonathan Bennion, Marisa Ferrara Boston, Mike Kuniavsky, Wiebke Hutiri, James Ezick, Malek Ben Salem, Rajat Sahay, Sujata S. Goswami, Usman Gohar, Ben Huang, Supheakmungkol Sarin, Elie Alhajjar, Canyu Chen, Roman Eng, Kashyap Ramanandula Manjusha, Virendra Mehta, Eileen Long, Murali Emani, Natan Vidra, Benjamin Rukundo, Abolfazl Shahbazi, Kongtao Chen, Rajat Ghosh, Vithursan Thangarasa, Pierre Peigné, Abhinav Singh, Max Bartolo, Satyapriya Krishna, Mubashara Akhtar, Rafael Gold, Cody Coleman, Luis Oala, Vassil Tashev, Joseph Marvin Imperial, Amy Russ, Sasidhar Kunapuli, Nicolas Miailhe, Julien Delaunay, Bhaktipriya Radharapu, Rajat Shinde, Tuesday, Debojyoti Dutta, Declan Grabb, Ananya Gangavarapu, Saurav Sahay, Agasthya Gangavarapu, Patrick Schramowski, Stephen Singam, Tom David, Xudong Han, Priyanka Mary Mammen, Tarunima Prabhakar, Venelin Kovatchev, Ahmed Ahmed, Kelvin N. Manyeki, Sandeep Madireddy, Foutse Khomh, Fedor Zhdanov, Joachim Baumann, Nina Vasan, Xianjun Yang, Carlos Mougn, Jibin Rajan Varghese, Hussain Chinoy, Seshakrishna Jitendar, Manil Maskey, Claire V. Hardgrove, Tianhao Li, Aakash Gupta, Emil Joswin, Yifan Mai, Shachi H. Kumar, Cigdem Patlak, Kevin Lu, Vincent Alessi, Sree Bhargavi Balija, Chenhe Gu, Robert Sullivan, James Gealy, Matt Lavrisa, James Goel, Peter Mattson, Percy Liang, Joaquin Vanschoren
2025	J	`jnl`	Auditing Google's AI Overviews and Featured Snippets: A Case Study on Baby Care and Pregnancy. CoRR Desheng Hu, Joachim Baumann, Aleksandra Urman, Elsa Lichtenegger, Robin Forsberg, Aniko Hannak, Christo Wilson
2025	J	`jnl`	Large Language Model Hacking: Quantifying the Hidden Risks of Using LLMs for Text Annotation. CoRR Joachim Baumann, Paul Röttger, Aleksandra Urman, Albert Wendsjö, Flor Miriam Plaza del Arco, Johannes B. Gruber, Dirk Hovy
2025	J	`jnl`	On prediction-modelers and decision-makers: why fairness requires more than a fair prediction model. AI Soc. Teresa Scantamburlo, Joachim Baumann, Christoph Heitz
2025	J	`jnl`	On the Societal Impact of Machine Learning. CoRR Joachim Baumann
2025	J	`jnl`	Reduced AI Acceptance After the Generative AI Boom: Evidence From a Two-Wave Survey Study. CoRR Joachim Baumann, Aleksandra Urman, Ulrich Leicht-Deobald, Zachary J. Roman, Anikó Hannák, Markus Christen
2025	J	`jnl`	SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviors. CoRR Tiancheng Hu, Joachim Baumann, Lorenzo Lupo, Nigel Collier, Dirk Hovy, Paul Röttger
2024	—	`conf`	Algorithmic Collective Action in Recommender Systems: Promoting Songs by Reordering Playlists. EWAF Joachim Baumann, Celestine Mendler-Dünner
2024	A*	`conf`	Algorithmic Collective Action in Recommender Systems: Promoting Songs by Reordering Playlists. NeurIPS Joachim Baumann, Celestine Mendler-Dünner
2024	J	`jnl`	Algorithmic Collective Action in Recommender Systems: Promoting Songs by Reordering Playlists. CoRR Joachim Baumann, Celestine Mendler-Dünner
2024	—	`conf`	Fairness in Online Ad Delivery. FAccT Joachim Baumann, Piotr Sapiezynski, Christoph Heitz, Aniko Hannak
2024	A*	`conf`	Identifying, Mitigating, and Anticipating Bias in Algorithmic Decisions. AAAI Joachim Baumann
2024	—	`conf`	On Prediction-modelers and Decision-makers: Why Fairness Requires More Than a Fair Prediction Model. EWAF Teresa Scantamburlo, Joachim Baumann, Christoph Heitz
2024	A*	`conf`	Preventing Eviction-Caused Homelessness through ML-Informed Distribution of Rental Assistance. AAAI Catalina Vajiac, Arun Frey, Joachim Baumann, Abigail Smith, Kasun Amarasinghe, Alice Lai, Kit T. Rodolfa, Rayid Ghani
2024	J	`jnl`	Preventing Eviction-Caused Homelessness through ML-Informed Distribution of Rental Assistance. CoRR Catalina Vajiac, Arun Frey, Joachim Baumann, Abigail Smith, Kasun Amarasinghe, Alice Lai, Kit T. Rodolfa, Rayid Ghani
2023	—	`conf`	A Classification of Feedback Loops and Their Relation to Biases in Automated Decision-Making Systems. EAAMO Nicolò Pagan, Joachim Baumann, Ezzat Elokda, Giulia De Pasquale, Saverio Bolognani, Anikó Hannák
2023	J	`jnl`	A Classification of Feedback Loops and Their Relation to Biases in Automated Decision-Making Systems. CoRR Nicolò Pagan, Joachim Baumann, Ezzat Elokda, Giulia De Pasquale, Saverio Bolognani, Anikó Hannák
2023	—	`conf`	An Open-Source Toolkit to Generate Biased Datasets. EWAF Joachim Baumann, Alessandro Castelnovo, Riccardo Crupi, Nicole Inverardi, Daniele Regoli
2023	A*	`conf`	Bias On Demand: Investigating Bias with a Synthetic Data Generator. IJCAI Joachim Baumann, Alessandro Castelnovo, Andrea Cosentini, Riccardo Crupi, Nicole Inverardi, Daniele Regoli
2023	—	`conf`	Bias on Demand: A Modelling Framework That Generates Synthetic Data With Bias. FAccT Joachim Baumann, Alessandro Castelnovo, Riccardo Crupi, Nicole Inverardi, Daniele Regoli
2023	—	`conf`	Closing the Loop: Feedback Loops and Biases in Automated Decision-Making. EWAF Nicolò Pagan, Joachim Baumann, Ezzat Elokda, Giulia De Pasquale, Saverio Bolognani, Anikó Hannák
2023	—	`conf`	Fair Machine Learning Through Post-processing: The Case of Predictive Parity. EWAF Joachim Baumann, Anikó Hannák, Christoph Heitz
2023	—	`conf`	FairnessLab: A Consequence-Sensitive Bias Audit and Mitigation Toolkit. EWAF Corinna Hertweck, Joachim Baumann, Michele Loi, Christoph Heitz
2023	J	`jnl`	On Prediction-Modelers and Decision-Makers: Why Fairness Requires More Than a Fair Prediction Model. CoRR Teresa Scantamburlo, Joachim Baumann, Christoph Heitz
2023	—	`conf`	Unification, Extension, and Interpretation of Group Fairness Metrics for ML-Based Decision-Making. EWAF Joachim Baumann, Corinna Hertweck, Michele Loi, Christoph Heitz
2022	J	`jnl`	A Justice-Based Framework for the Analysis of Algorithmic Fairness-Utility Trade-Offs. CoRR Corinna Hertweck, Joachim Baumann, Michele Loi, Eleonora Viganò, Christoph Heitz
2022	J	`jnl`	Distributive Justice as the Foundational Premise of Fair ML: Unification, Extension, and Interpretation of Group Fairness Metrics. CoRR Joachim Baumann, Corinna Hertweck, Michele Loi, Christoph Heitz
2022	—	`conf`	Enforcing Group Fairness in Algorithmic Decision Making: Utility Maximization Under Sufficiency. FAccT Joachim Baumann, Anikó Hannák, Christoph Heitz
2022	J	`jnl`	Enforcing Group Fairness in Algorithmic Decision Making: Utility Maximization Under Sufficiency. CoRR Joachim Baumann, Anikó Hannák, Christoph Heitz
2022	—	`conf`	Group Fairness in Prediction-Based Decision Making: From Moral Assessment to Implementation. SDS Joachim Baumann, Christoph Heitz
2022	J	`jnl`	Group Fairness in Prediction-Based Decision Making: From Moral Assessment to Implementation. CoRR Joachim Baumann, Christoph Heitz
2021	—	`conf`	Dealers of Peaches and Lemons: How Can Used Car Dealers Use Trusted Car Data to create value? HICSS Joachim Baumann, Liudmila Zavolokina, Gerhard Schwabe