Lauro Langosco di Langosco

According to our database, Lauro Langosco di Langosco authored at least 6 papers between 2021 and 2023.

Collaborative distances:

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

2023

Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback.

Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell

CoRR, 2023

Unifying Grokking and Double Descent.

Xander Davies, Lauro Langosco, David Krueger

CoRR, 2023

Harms from Increasingly Agentic Algorithmic Systems.

Alan Chan, Rebecca Salganik, Alva Markelius, Chris Pang, Nitarshan Rajkumar, Dmitrii Krasheninnikov, Lauro Langosco, Zhonghao He, Yawen Duan, Micah Carroll, Michelle Lin, Alex Mayhew, Katherine M. Collins, Maryam Molamohammadi, John Burden, Wanru Zhao, Shalaleh Rismani, Konstantinos Voudouris, Umang Bhatt, Adrian Weller, David Krueger, Tegan Maharaj

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

2022

Goal Misgeneralization in Deep Reinforcement Learning.

Lauro Langosco di Langosco, Jack Koch, Lee D. Sharkey, Jacob Pfau, David Krueger

Proceedings of the International Conference on Machine Learning, 2022

2021

Neural Variational Gradient Descent.

Lauro Langosco di Langosco, Vincent Fortuin, Heiko Strathmann

CoRR, 2021

Objective Robustness in Deep Reinforcement Learning.

Jack Koch, Lauro Langosco, Jacob Pfau, James Le, Lee Sharkey

CoRR, 2021