Linear Ranking for Linear Lasso Programs. - Matthias Heizmann; Jochen Hoenicke; Jan Leike; Andreas Podelski (ATVA, 2013)

Indefinitely Oscillating Martingales. - Jan Leike; Marcus Hutter (ALT, 2014)

Synthesis for Polynomial Lasso Programs. - Jan Leike; Ashish Tiwari 001 (VMCAI, 2014)

Ranking Function Synthesis for Linear Lasso Programs. - Jan Leike (CoRR, 2014)

Geometric Series as Nontermination Arguments for Linear Lasso Programs. - Jan Leike; Matthias Heizmann (CoRR, 2014)

A Definition of Happiness for Reinforcement Learning Agents. - Mayank Daswani; Jan Leike (AGI, 2015)

Sequential Extensions of Causal and Evidential Decision Theory. - Tom Everitt; Jan Leike; Marcus Hutter (ADT, 2015)

Solomonoff Induction Violates Nicod's Criterion. - Jan Leike; Marcus Hutter (ALT, 2015)

On the Computability of Solomonoff Induction and Knowledge-Seeking. - Jan Leike; Marcus Hutter (ALT, 2015)

Bad Universal Priors and Notions of Optimality. - Jan Leike; Marcus Hutter (COLT, 2015)

Ultimate Automizer with Array Interpolation - (Competition Contribution). - Matthias Heizmann; Daniel Dietsch; Jan Leike; Betim Musa; Andreas Podelski (TACAS, 2015)

On the Computability of AIXI. - Jan Leike; Marcus Hutter (UAI, 2015)

Ranking Templates for Linear Loops. - Jan Leike; Matthias Heizmann (Log. Methods Comput. Sci., 2015)

Loss Bounds and Time Complexity for Speed Priors. - Daniel Filan; Jan Leike; Marcus Hutter (AISTATS, 2016)

Ultimate Automizer with Two-track Proofs - (Competition Contribution). - Matthias Heizmann; Daniel Dietsch; Marius Greitschus; Jan Leike; Betim Musa; Claus Schätzle; Andreas Podelski (TACAS, 2016)

Thompson Sampling is Asymptotically Optimal in General Environments. - Jan Leike; Tor Lattimore; Laurent Orseau; Marcus Hutter (UAI, 2016)

A Formal Solution to the Grain of Truth Problem. - Jan Leike; Jessica Taylor; Benya Fallenstein (UAI, 2016)

Exploration Potential. - Jan Leike (CoRR, 2016)

Nonparametric General Reinforcement Learning. - Jan Leike (CoRR, 2016)

Generalised Discount Functions applied to a Monte-Carlo AI u Implementation. - Sean Lamont; John Aslanides; Jan Leike; Marcus Hutter (AAMAS, 2017)

Universal Reinforcement Learning Algorithms: Survey and Experiments. - John Aslanides; Jan Leike; Marcus Hutter (IJCAI, 2017)

On Thompson Sampling and Asymptotic Optimality. - Jan Leike; Tor Lattimore; Laurent Orseau; Marcus Hutter (IJCAI, 2017)

Deep Reinforcement Learning from Human Preferences. - Paul F. Christiano; Jan Leike; Tom B. Brown; Miljan Martic; Shane Legg; Dario Amodei (NIPS, 2017)

Generalised Discount Functions applied to a Monte-Carlo AImu Implementation. - Sean Lamont; John Aslanides; Jan Leike; Marcus Hutter (CoRR, 2017)

AI Safety Gridworlds. - Jan Leike; Miljan Martic; Victoria Krakovna; Pedro A. Ortega; Tom Everitt; Andrew Lefrancq; Laurent Orseau; Shane Legg (CoRR, 2017)

Jointly Learning "What" and "How" from Instructions and Goal-States. - Dzmitry Bahdanau; Felix Hill; Jan Leike; Edward Hughes 001; Pushmeet Kohli; Edward Grefenstette (ICLR (Workshop), 2018)

Reward learning from human preferences and demonstrations in Atari. - Borja Ibarz; Jan Leike; Tobias Pohlen; Geoffrey Irving; Shane Legg; Dario Amodei (NeurIPS, 2018)

Geometric Nontermination Arguments. - Jan Leike; Matthias Heizmann (TACAS (2), 2018)

Learning to Follow Language Instructions with Adversarial Reward Induction. - Dzmitry Bahdanau; Felix Hill; Jan Leike; Edward Hughes 001; Pushmeet Kohli; Edward Grefenstette (CoRR, 2018)

Scalable agent alignment via reward modeling: a research direction. - Jan Leike; David Krueger 001; Tom Everitt; Miljan Martic; Vishal Maini; Shane Legg (CoRR, 2018)

Scaling shared model governance via model splitting. - Miljan Martic; Jan Leike; Andrew Trask; Matteo Hessel; Shane Legg; Pushmeet Kohli (CoRR, 2018)

On the computability of Solomonoff induction and AIXI. - Jan Leike; Marcus Hutter (Theor. Comput. Sci., 2018)

Learning to Understand Goal Specifications by Modelling Reward. - Dzmitry Bahdanau; Felix Hill; Jan Leike; Edward Hughes 001; Seyed Arian Hosseini; Pushmeet Kohli; Edward Grefenstette (ICLR (Poster), 2019)

Learning Human Objectives by Evaluating Hypothetical Behavior. - Siddharth Reddy; Anca D. Dragan; Sergey Levine; Shane Legg; Jan Leike (ICML, 2020)

Pitfalls of Learning a Reward Function Online. - Stuart Armstrong; Jan Leike; Laurent Orseau; Shane Legg (IJCAI, 2020)

Hidden Incentives for Auto-Induced Distributional Shift. - David Krueger 001; Tegan Maharaj; Jan Leike (CoRR, 2020)

Active Reinforcement Learning: Observing Rewards at a Cost. - David Krueger 001; Jan Leike; Owain Evans; John Salvatier (CoRR, 2020)

Quantifying Differences in Reward Functions. - Adam Gleave; Michael Dennis 001; Shane Legg; Stuart Russell 001; Jan Leike (ICLR, 2021)

Institutionalising Ethics in AI through Broader Impact Requirements. - Carina E. A. Prunkl; Carolyn Ashurst; Markus Anderljung; Helena Webb; Jan Leike; Allan Dafoe (CoRR, 2021)

Evaluating Large Language Models Trained on Code. - Mark Chen 003; Jerry Tworek; Heewoo Jun; Qiming Yuan; Henrique Pondé de Oliveira Pinto; Jared Kaplan; Harri Edwards; Yuri Burda; Nicholas Joseph; Greg Brockman; Alex Ray; Raul Puri; et al. (CoRR, 2021)

Recursively Summarizing Books with Human Feedback. - Jeff Wu 003; Long Ouyang; Daniel M. Ziegler; Nisan Stiennon; Ryan Lowe; Jan Leike; Paul F. Christiano (CoRR, 2021)

Institutionalizing ethics in AI through broader impact requirements. - Carina E. A. Prunkl; Carolyn Ashurst; Markus Anderljung; Helena Webb; Jan Leike; Allan Dafoe (Nat. Mach. Intell., 2021)

Training language models to follow instructions with human feedback. - Long Ouyang; Jeffrey Wu 003; Xu Jiang; Diogo Almeida; Carroll L. Wainwright; Pamela Mishkin; Chong Zhang; Sandhini Agarwal; Katarina Slama; Alex Ray; John Schulman; Jacob Hilton; et al. (NeurIPS, 2022)

Safe Deep RL in 3D Environments using Human Feedback. - Matthew Rahtz; Vikrant Varma; Ramana Kumar; Zachary Kenton; Shane Legg; Jan Leike (CoRR, 2022)

Self-critiquing models for assisting human evaluators. - William Saunders; Catherine Yeh; Jeff Wu 003; Steven Bills; Long Ouyang; Jonathan Ward; Jan Leike (CoRR, 2022)

Let's Verify Step by Step. - Hunter Lightman; Vineet Kosaraju; Yuri Burda; Harrison Edwards; Bowen Baker; Teddy Lee; Jan Leike; John Schulman; Ilya Sutskever; Karl Cobbe (ICLR, 2024)

Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision. - Collin Burns; Pavel Izmailov; Jan Hendrik Kirchner; Bowen Baker; Leo Gao; Leopold Aschenbrenner; Yining Chen; Adrien Ecoffet; Manas Joglekar; Jan Leike; Ilya Sutskever; Jeffrey Wu 003 (ICML, 2024)

LLM Critics Help Catch LLM Bugs. - Nat McAleese; Rai Michael Pokorny; Juan Felipe Ceron Uribe; Evgenia Nitishinskaya; Maja Trebacz; Jan Leike (CoRR, 2024)

Prover-Verifier Games improve legibility of LLM outputs. - Jan Hendrik Kirchner; Yining Chen; Harri Edwards; Jan Leike; Nat McAleese; Yuri Burda (CoRR, 2024)

Scaling and evaluating sparse autoencoders. - Leo Gao; Tom Dupré la Tour; Henk Tillman; Gabriel Goh; Rajan Troll; Alec Radford; Ilya Sutskever; Jan Leike; Jeffrey Wu 003 (ICLR, 2025)

Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming. - Mrinank Sharma; Meg Tong; Jesse Mu; Jerry Wei; Jorrit Kruthoff; Scott Goodfriend; Euan Ong; Alwin Peng; Raj Agarwal; Cem Anil; Amanda Askell; Nathan Bailey; et al. (CoRR, 2025)

Forecasting Rare Language Model Behaviors. - Erik Jones; Meg Tong; Jesse Mu; Mohammed Mahfoud; Jan Leike; Roger B. Grosse; Jared Kaplan; William Fithian; Ethan Perez; Mrinank Sharma (CoRR, 2025)

Auditing language models for hidden objectives. - Samuel Marks; Johannes Treutlein; Trenton Bricken; Jack Lindsey; Jonathan Marcus; Siddharth Mishra-Sharma; Daniel M. Ziegler; Emmanuel Ameisen; Joshua Batson; Tim Belonax; Samuel R. Bowman; Shan Carter; et al. (CoRR, 2025)

Reasoning Models Don't Always Say What They Think. - Yanda Chen; Joe Benton; Ansh Radhakrishnan; Jonathan Uesato; Carson Denison; John Schulman; Arushi Somani; Peter Hase; Misha Wagner; Fabien Roger; Vladimir Mikulik; Samuel R. Bowman; et al. (CoRR, 2025)

Unsupervised Elicitation of Language Models. - Jiaxin Wen; Zachary Ankner; Arushi Somani; Peter Hase; Samuel Marks; Jacob Goldman-Wetzler; Linda Petrini; Henry Sleight; Collin Burns; He He 001; Shi Feng 005; Ethan Perez; et al. (CoRR, 2025)