Help or Hinder: Bayesian Models of Social Goal Inference. - Tomer D. Ullman; Chris L. Baker; Owen Macindoe; Owain Evans; Noah D. Goodman; Joshua B. Tenenbaum (NIPS, 2009)

Learning the Preferences of Ignorant, Inconsistent Agents. - Owain Evans; Andreas Stuhlmüller; Noah D. Goodman (AAAI, 2016)

Agent-Agnostic Human-in-the-Loop Reinforcement Learning. - David Abel; John Salvatier; Andreas Stuhlmüller; Owain Evans (CoRR, 2017)

When Will AI Exceed Human Performance? Evidence from AI Experts. - Katja Grace; John Salvatier; Allan Dafoe; Baobao Zhang; Owain Evans (CoRR, 2017)

Trial without Error: Towards Safe Reinforcement Learning via Human Intervention. - William Saunders; Girish Sastry; Andreas Stuhlmüller; Owain Evans (AAMAS, 2018)

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation. - Miles Brundage; Shahar Avin; Jack Clark; Helen Toner; Peter Eckersley; Ben Garfinkel; Allan Dafoe; Paul Scharre; Thomas Zeitzoff; Bobby Filar; Hyrum S. Anderson; Heather Roff; et al. (CoRR, 2018)

Active Reinforcement Learning with Monte-Carlo Tree Search. - Sebastian Schulze; Owain Evans (CoRR, 2018)

Viewpoint: When Will AI Exceed Human Performance? Evidence from AI Experts. - Katja Grace; John Salvatier; Allan Dafoe; Baobao Zhang; Owain Evans (J. Artif. Intell. Res., 2018)

Generalizing from a few environments in safety-critical reinforcement learning. - Zachary Kenton; Angelos Filos; Owain Evans; Yarin Gal (CoRR, 2019)

Sensory Optimization: Neural Networks as a Model for Understanding and Creating Art. - Owain Evans (CoRR, 2019)

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

Truthful AI: Developing and governing AI that does not lie. - Owain Evans; Owen Cotton-Barratt; Lukas Finnveden; Adam Bales; Avital Balwit; Peter Wills; Luca Righetti; William Saunders (CoRR, 2021)

TruthfulQA: Measuring How Models Mimic Human Falsehoods. - Stephanie Lin; Jacob Hilton; Owain Evans (ACL (1), 2022)

Forecasting Future World Events With Neural Networks. - Andy Zou; Tristan Xiao; Ryan Jia; Joe Kwon; Mantas Mazeika; Richard Li; Dawn Song; Jacob Steinhardt; Owain Evans; Dan Hendrycks (NeurIPS, 2022)

Teaching Models to Express Their Uncertainty in Words. - Stephanie Lin; Jacob Hilton; Owain Evans (Trans. Mach. Learn. Res., 2022)

Taken out of context: On measuring situational awareness in LLMs. - Lukas Berglund; Asa Cooper Stickland; Mikita Balesni; Maximilian Kaufmann; Meg Tong; Tomasz Korbak; Daniel Kokotajlo; Owain Evans (CoRR, 2023)

Tell, don't show: Declarative facts influence how LLMs generalize. - Alexander Meinke; Owain Evans (CoRR, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A". - Lukas Berglund; Meg Tong; Maximilian Kaufmann; Mikita Balesni; Asa Cooper Stickland; Tomasz Korbak; Owain Evans (ICLR, 2024)

How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions. - Lorenzo Pacchiardi; Alex James Chan; Sören Mindermann; Ilan Moscovitz; Alexa Y. Pan; Yarin Gal; Owain Evans; Jan Markus Brauner (ICLR, 2024)

Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs. - Rudolf Laine; Bilal Chughtai; Jan Betley; Kaivalya Hariharan; Mikita Balesni; Jérémy Scheurer; Marius Hobbhahn; Alexander Meinke; Owain Evans (NeurIPS, 2024)

Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data. - Johannes Treutlein; Dami Choi; Jan Betley; Samuel Marks; Cem Anil; Roger B. Grosse; Owain Evans (NeurIPS, 2024)

Can Language Models Explain Their Own Classification Behavior? - Dane Sherburn; Bilal Chughtai; Owain Evans (CoRR, 2024)

Looking Inward: Language Models Can Learn About Themselves by Introspection. - Felix J. Binder; James Chua; Tomasz Korbak; Henry Sleight; John Hughes; Robert Long; Ethan Perez; Miles Turpin; Owain Evans (CoRR, 2024)

Towards evaluations-based safety cases for AI scheming. - Mikita Balesni; Marius Hobbhahn; David Lindner; Alexander Meinke; Tomek Korbak; Joshua Clymer; Buck Shlegeris; Jérémy Scheurer; Charlotte Stix; Rusheb Shah; Nicholas Goldowsky-Dill; Dan Braun; et al. (CoRR, 2024)

The Two-Hop Curse: LLMs trained on A->B, B->C fail to learn A->C. - Mikita Balesni; Tomasz Korbak; Owain Evans (CoRR, 2024)

Tell me about yourself: LLMs are aware of their learned behaviors. - Jan Betley; Xuchan Bao; Martín Soto; Anna Sztyber-Betley; James Chua; Owain Evans (ICLR, 2025)

Looking Inward: Language Models Can Learn About Themselves by Introspection. - Felix Jedidja Binder; James Chua; Tomek Korbak; Henry Sleight; John Hughes; Robert Long; Ethan Perez; Miles Turpin; Owain Evans (ICLR, 2025)

Inference-Time-Compute: More Faithful? A Research Note. - James Chua; Owain Evans (CoRR, 2025)

Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs. - Jan Betley; Daniel Tan; Niels Warncke; Anna Sztyber-Betley; Xuchan Bao; Martín Soto; Nathan Labenz; Owain Evans (CoRR, 2025)

Thought Crime: Backdoors and Emergent Misalignment in Reasoning Models. - James Chua; Jan Betley; Mia Taylor; Owain Evans (CoRR, 2025)

Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety. - Tomek Korbak; Mikita Balesni; Elizabeth Barnes; Yoshua Bengio; Joe Benton; Joseph Bloom; Mark Chen 003; Alan Cooney; Allan Dafoe; Anca D. Dragan; Scott Emmons; Owain Evans; et al. (CoRR, 2025)

Subliminal Learning: Language models transmit behavioral traits via hidden signals in data. - Alex Cloud; Minh Le; James Chua; Jan Betley; Anna Sztyber-Betley; Jacob Hilton; Samuel Marks; Owain Evans (CoRR, 2025)

Persona Vectors: Monitoring and Controlling Character Traits in Language Models. - Runjin Chen; Andy Arditi; Henry Sleight; Owain Evans; Jack Lindsey (CoRR, 2025)