Mikulik, Vladimir
- Scaling Language Models: Methods, Analysis & Insights from Training Gopher
2021/12/08 by Jack W. Rae, Sebastian Borgeaud, Rae, Jack W. +157 · 73 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Topic Modeling
- Risks from Learned Optimization in Advanced Machine Learning Systems
2019/06/05 by Evan Hubinger, Hubinger, Evan, Chris van Merwijk +7 · 35 citations
Computer Science · #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning and Algorithms #Reinforcement Learning in Robotics
- Algorithms for Causal Reasoning in Probability Trees
2020/10/23 by Tim Genewein, Genewein, Tim, Tom McGrath +11 · 2 voices
#cs.AI #cs.LG
- Tracr: Compiled Transformers as a Laboratory for Interpretability
2023/01/12 by David Lindner, Lindner, David, János Kramár +9 · 1 voice · 5 citations
Computer Science · Mathematics · #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #cs.AI #cs.LG #stat.ML
- Alignment of Language Agents
2021/03/26 by Kenton, Zachary, Everitt, Tom, Weidinger, Laura +3 · 14 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Teaching language models to support answers with verified quotes
2022/03/21 by Menick, Jacob, Trebacz, Maja, Mikulik, Vladimir +8 · 14 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla
2023/07/18 by Tom Lieberum, Matthew Rahtz, Lieberum, Tom +11 · 16 citations
Computer Science · Engineering · Materials Science · #FOS: Computer and information sciences #Ferroelectric and Negative Capacitance Devices #Machine Learning (cs.LG) #Machine Learning in Materials Science #Topic Modeling
- The Hydra Effect: Emergent Self-repair in Language Model Computations
2023/07/28 by McGrath, Thomas, Rahtz, Matthew, Kramar, Janos +2 · 12 citations
#Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Gemini: A Family of Highly Capable Multimodal Models
2023/12/19 by Rohan Anil, Gemini Team, 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
- An Approach to Technical AGI Safety and Security
2025/04/02 by Shah, Rohin, Irpan, Alex, Turner, Alexander Matt +27 · 17 citations
#Artificial Intelligence (cs.AI) #Computers and Society (cs.CY) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Challenges with unsupervised LLM knowledge discovery
2023/12/15 by Sebastian Farquhar, Vikrant Varma, Farquhar, Sebastian +9 · 6 citations
Computer Science · Materials Science · #Topic Modeling #Natural Language Processing Techniques #Machine Learning in Materials Science
- Neural networks are a priori biased towards Boolean functions with low entropy
2019/09/25 by Mingard, Chris, Skalse, Joar, Valle-Pérez, Guillermo +3 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Meta-trained agents implement Bayes-optimal agents
2020/10/21 by Vladimir Mikulik, Mikulik, Vladimir, Grégoire Delétang +11 · 1 citation
Computer Science · #Artificial Intelligence (cs.AI) #Data Stream Mining Techniques #Domain Adaptation and Few-Shot Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural and Evolutionary Computing (cs.NE)