Madras, David

1. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
   2025/07/07 by Gheorghe Comanici, Eric Bieber, Comanici, Gheorghe +6844 · 8 voices · 1370 citations
   #cs.CL #cs.AI
2. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
   2024/03/08 by Gemini Robotics Team, Petko Georgiev, Gemini Team +2277 · 4 voices · 559 citations
   Computer Science · #Semantic Web and Ontologies
3. Learning Adversarially Fair and Transferable Representations
   2018/02/17 by Madras, David, Creager, Elliot, Pitassi, Toniann +1 · 24 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
4. Predict Responsibly: Improving Fairness and Accuracy by Learning to\n Defer
   2017/11/17 by David Madras, Toniann Pitassi, Madras, David +3 · 24 citations
   Social Sciences · Neuroscience · Economics, Econometrics and Finance · #Ethics and Social Impacts of AI #Psychology of Moral and Emotional Judgment #Law, Economics, and Judicial Systems
5. Gemini: A Family of Highly Capable Multimodal Models
   2023/12/19 by Gemini Team, Rohan Anil, Anil, Rohan +2682 · 9 voices
   Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #cs.AI #cs.CL #cs.CV
6. Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
   2020/06/18 by Sindy Löwe, David Madras, Löwe, Sindy +5 · 7 citations
   Computer Science · Decision Sciences · #Bayesian Modeling and Causal Inference #Data Quality and Management #Advanced Graph Neural Networks
7. Learning and Forgetting Unsafe Examples in Large Language Models
   2023/12/20 by Zhao, Jiachen, Deng, Zhun, Madras, David +2 · 3 citations
   #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
8. Fairness Through Causal Awareness: Learning Latent-Variable Models for Biased Data
   2018/09/07 by Madras, David, Creager, Elliot, Pitassi, Toniann +1 · 1 citation
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
9. Understanding challenges to the interpretation of disaggregated evaluations of algorithmic fairness
   2025/06/04 by Stephen R. Pfohl, Natalie Harris, Pfohl, Stephen R. +27 · 1 voice · 3 citations
   #stat.ML #cs.CY #cs.LG