Markus Kunesch

According to our database, Markus Kunesch authored at least 12 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

LearnLM: Improving Gemini for Learning.

Abhinit Modi, Aditya Srikanth Veerubhotla, Aliya Rysbek, Andrea Huber, Brett Wiltshire, Brian Veprek, Daniel Gillick, Daniel Kasenberg, Derek Ahmed, Irina Jurenka, James Cohan, Jennifer She, Julia Wilkowski, Kaiz Alarakyia, Kevin R. McKee, Lisa Wang, Markus Kunesch, Mike Schaekermann, Miruna Pîslar, Nikhil Joshi, Parsa Mahmoudieh, Paul Jhun, Sara Wiltberger, Shakir Mohamed, Shashank Agarwal, Shubham Milind Phal, Sun Jae Lee, Theofilos Strinopoulos, Wei-Jen Ko, Amy Wang, Ankit Anand, Avishkar Bhoopchand, Dan Wild, Divya Pandya, Filip Bar, Garth Graham, Holger Winnemoeller, Mahvish Nagda, Prateek Kolhar, Renee Schneider, Shaojian Zhu, Stephanie Chan, Steve Yadlowsky, Viknesh Sounderajah, Yannis Assael

CoRR, 2024

Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach.

Irina Jurenka, Markus Kunesch, Kevin R. McKee, Daniel Gillick, Shaojian Zhu, Sara Wiltberger, Shubham Milind Phal, Katherine L. Hermann, Daniel Kasenberg, Avishkar Bhoopchand, Ankit Anand, Miruna Pîslar, Stephanie Chan, Lisa Wang, Jennifer She, Parsa Mahmoudieh, Aliya Rysbek, Wei-Jen Ko, Andrea Huber, Brett Wiltshire, Gal Elidan, Roni Rabin, Jasmin Rubinovitz, Amit Pitaru, Mac McAllister, Julia Wilkowski, David Choi, Roee Engelberg, Lidan Hackmon, Adva Levin, Rachel Griffin, Michael Sears, Filip Bar, Mia Mesar, Mana Jabbour, Arslan Chaudhry, James Cohan, Sridhar Thiagarajan, Nir Levine, Ben Brown, Dilan Görür, Svetlana Grant, Rachel Hashimshoni, Laura Weidinger, Jieru Hu, Dawn Chen, Kuba Dolecki, Canfer Akbulut, Maxwell L. Bileschi, Laura Culp, Wen-Xin Dong, Nahema Marchal, Kelsie Van Deman, Hema Bajaj Misra, Michael Duah, Moran Ambar, Avi Caciularu, Sandra Lefdal, Christopher Summerfield, James An, Pierre-Alexandre Kamienny, Abhinit Mohdi, Theofilos Strinopoulos, Annie Hale, Wayne Anderson, Luis C. Cobo, Niv Efron, Muktha Ananda, Shakir Mohamed, Maureen Heymans, Zoubin Ghahramani, Yossi Matias, Ben Gomes, Lila Ibrahim

CoRR, 2024

2023

The Puzzle of Evaluating Moral Cognition in Artificial Agents.

Madeline G. Reinecke, Yiran Mao, Markus Kunesch, Edgar A. Duéñez-Guzmán, Julia Haas, Joel Z. Leibo

Cogn. Sci., August, 2023

Doing the right thing for the right reason: Evaluating artificial moral cognition by probing cost insensitivity.

Yiran Mao, Madeline G. Reinecke, Markus Kunesch, Edgar A. Duéñez-Guzmán, Ramona Comanescu, Julia Haas, Joel Z. Leibo

CoRR, 2023

Representation in AI Evaluations.

A. Stevie Bergman, Lisa Anne Hendricks, Maribeth Rauh, Boxi Wu, William Agnew, Markus Kunesch, Isabella Duan, Iason Gabriel, William Isaac

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022

Your Policy Regularizer is Secretly an Adversary.

Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Shane Legg, Pedro A. Ortega

Trans. Mach. Learn. Res., 2022

Beyond Bayes-optimality: meta-learning what you know you don't know.

Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Tim Genewein, Elliot Catt, Kevin Li, Anian Ruoss, Chris Cundy, Joel Veness, Jane X. Wang, Marcus Hutter, Christopher Summerfield, Shane Legg, Pedro A. Ortega

CoRR, 2022

2021

GRChombo: An adaptable numerical relativity code for fundamental physics.

Tomas Andrade, Llibert Aresté Saló, Josu C. Aurrekoetxea, Jamie Bamber, Katy Clough, Robin Croft, Eloy de Jong, Amelia Drew, Alejandro Duran, Pedro Ferreira, Pau Figueras, Hal Finkel, Tiago França, Bo-Xuan Ge, Chenxia Gu, Thomas Helfer, Juha Jäykkä, Cristian Joana, Markus Kunesch, Kacper Kornet, Eugene Lim, Francesco Muia, Zainab Nazari, Miren Radia, Justin Ripley, Paul Shellard, Ulrich Sperhake, Dina Traykova, Saran Tunyasuvunakool, Zipeng Wang, James Widdicombe, Kaze Wong

J. Open Source Softw., 2021

Model-Free Risk-Sensitive Reinforcement Learning.

Grégoire Delétang, Jordi Grau-Moya, Markus Kunesch, Tim Genewein, Rob Brekelmans, Shane Legg, Pedro A. Ortega

CoRR, 2021

Shaking the foundations: delusions in sequence models for interaction and control.

Pedro A. Ortega, Markus Kunesch, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Joel Veness, Jonas Buchli, Jonas Degrave, Bilal Piot, Julien Pérolat, Tom Everitt, Corentin Tallec, Emilio Parisotto, Tom Erez, Yutian Chen, Scott E. Reed, Marcus Hutter, Nando de Freitas, Shane Legg

CoRR, 2021

Causal Analysis of Agent Behavior for AI Safety.

Grégoire Delétang, Jordi Grau-Moya, Miljan Martic, Tim Genewein, Tom McGrath, Vladimir Mikulik, Markus Kunesch, Shane Legg, Pedro A. Ortega

CoRR, 2021

2020

Human-interpretable model explainability on high-dimensional data.

Damien de Mijolla, Christopher Frye, Markus Kunesch, John Mansir, Ilya Feige

CoRR, 2020