Dmitrii Krasheninnikov

According to our database, Dmitrii Krasheninnikov authored at least 12 papers between 2019 and 2025.

Collaborative distances:

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

2025

Detecting High-Stakes Interactions with Activation Probes.

Alex McKenzie, Urja Pawar, Phil Blandfort, William Bankes, David Krueger, Ekdeep Singh Lubana, Dmitrii Krasheninnikov

CoRR, June, 2025

Understanding (Un)Reliability of Steering Vectors in Language Models.

Joschka Braun, Carsten Eickhoff, David Krueger, Seyed Ali Bahrainian, Dmitrii Krasheninnikov

CoRR, May, 2025

2024

Comparing Bottom-Up and Top-Down Steering Approaches on In-Context Learning Tasks.

Madeline Brumley, Joe Kwon, David Krueger, Dmitrii Krasheninnikov, Usman Anwar

CoRR, 2024

Stress-Testing Capability Elicitation With Password-Locked Models.

Ryan Greenblatt, Fabien Roger, Dmitrii Krasheninnikov, David Krueger

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Implicit meta-learning may lead language models to trust more reliable sources.

Dmitrii Krasheninnikov, Egor Krasheninnikov, Bruno Kacper Mlodozeniec, Tegan Maharaj, David Krueger

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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 Tong 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

Trans. Mach. Learn. Res., 2023

Meta- (out-of-context) learning in neural networks.

Dmitrii Krasheninnikov, Egor Krasheninnikov, Bruno Mlodozeniec, 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 P. 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

Defining and Characterizing Reward Hacking.

Joar Skalse, Nikolaus H. R. Howe, Dmitrii Krasheninnikov, David Krueger

CoRR, 2022

Defining and Characterizing Reward Gaming.

Joar Skalse, Nikolaus H. R. Howe, Dmitrii Krasheninnikov, David Krueger

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Combining Reward Information from Multiple Sources.

Dmitrii Krasheninnikov, Rohin Shah, Herke van Hoof

CoRR, 2021

2019

Preferences Implicit in the State of the World.

Rohin Shah, Dmitrii Krasheninnikov, Jordan Alexander, Pieter Abbeel, Anca D. Dragan

Proceedings of the 7th International Conference on Learning Representations, 2019