Electrical flows, laplacian systems, and faster approximation of maximum flow in undirected graphs. - Paul F. Christiano; Jonathan A. Kelner; Aleksander Madry; Daniel A. Spielman; Shang-Hua Teng (STOC, 2011)

Lossless Fault-Tolerant Data Structures with Additive Overhead. - Paul F. Christiano; Erik D. Demaine; Shaunak Kishore (WADS, 2011)

Quantum Money from Hidden Subspaces. - Scott Aaronson; Paul F. Christiano (Electron. Colloquium Comput. Complex., 2012)

Open Problem: Online Local Learning. - Paul F. Christiano (COLT, 2014)

Online local learning via semidefinite programming. - Paul F. Christiano (STOC, 2014)

Robust Cooperation in the Prisoner's Dilemma: Program Equilibrium via Provability Logic. - Mihály Bárász; Paul F. Christiano; Benja Fallenstein; Marcello Herreshoff; Patrick LaVictoire; Eliezer Yudkowsky (CoRR, 2014)

Reflective Oracles: A Foundation for Game Theory in Artificial Intelligence. - Benja Fallenstein; Jessica Taylor; Paul F. Christiano (LORI, 2015)

Reflective Oracles: A Foundation for Classical Game Theory. - Benja Fallenstein; Jessica Taylor; Paul F. Christiano (CoRR, 2015)

Provably manipulation-resistant reputation systems. - Paul F. Christiano (COLT, 2016)

Theano: A Python framework for fast computation of mathematical expressions. - Rami Al-Rfou; Guillaume Alain; Amjad Almahairi; Christof Angermüller; Dzmitry Bahdanau; Nicolas Ballas; Frédéric Bastien; Justin Bayer; Anatoly Belikov; Alexander Belopolsky; Yoshua Bengio; Arnaud Bergeron; et al. (CoRR, 2016)

Concrete Problems in AI Safety. - Dario Amodei; Chris Olah; Jacob Steinhardt; Paul F. Christiano; John Schulman; Dan Mané (CoRR, 2016)

Robust Collaborative Online Learning. - Paul F. Christiano (CoRR, 2016)

Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model. - Paul F. Christiano; Zain Shah; Igor Mordatch; Jonas Schneider 002; Trevor Blackwell; Joshua Tobin; Pieter Abbeel; Wojciech Zaremba (CoRR, 2016)

A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models. - Chelsea Finn; Paul F. Christiano; Pieter Abbeel; Sergey Levine (CoRR, 2016)

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

Manipulation-resistant online learning. - Paul Francis Christiano (2017)

Certifiable Randomness from a Single Quantum Device. - Zvika Brakerski; Paul F. Christiano; Urmila Mahadev; Umesh V. Vazirani; Thomas Vidick (CoRR, 2018)

AI safety via debate. - Geoffrey Irving; Paul F. Christiano; Dario Amodei (CoRR, 2018)

Unrestricted Adversarial Examples. - Tom B. Brown; Nicholas Carlini; Chiyuan Zhang; Catherine Olsson; Paul F. Christiano; Ian J. Goodfellow (CoRR, 2018)

Supervising strong learners by amplifying weak experts. - Paul F. Christiano; Buck Shlegeris; Dario Amodei (CoRR, 2018)

Fine-Tuning Language Models from Human Preferences. - Daniel M. Ziegler; Nisan Stiennon; Jeffrey Wu 003; Tom B. Brown; Alec Radford; Dario Amodei; Paul F. Christiano; Geoffrey Irving (CoRR, 2019)

Learning to summarize with human feedback. - Nisan Stiennon; Long Ouyang; Jeffrey Wu 003; Daniel M. Ziegler; Ryan Lowe; Chelsea Voss; Alec Radford; Dario Amodei; Paul F. Christiano (NeurIPS, 2020)

Learning to summarize from human feedback. - Nisan Stiennon; Long Ouyang; Jeff Wu 003; Daniel M. Ziegler; Ryan Lowe; Chelsea Voss; Alec Radford; Dario Amodei; Paul F. Christiano (CoRR, 2020)

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)

A Cryptographic Test of Quantumness and Certifiable Randomness from a Single Quantum Device. - Zvika Brakerski; Paul F. Christiano; Urmila Mahadev; Umesh V. Vazirani; Thomas Vidick (J. ACM, 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)

Formalizing the presumption of independence. - Paul F. Christiano; Eric Neyman; Mark Xu (CoRR, 2022)

Model evaluation for extreme risks. - Toby Shevlane; Sebastian Farquhar; Ben Garfinkel; Mary Phuong; Jess Whittlestone; Jade Leung; Daniel Kokotajlo; Nahema Marchal; Markus Anderljung; Noam Kolt; Lewis Ho; Divya Siddarth; et al. (CoRR, 2023)

Evaluating Language-Model Agents on Realistic Autonomous Tasks. - Megan Kinniment; Lucas Jun Koba Sato; Haoxing Du; Brian Goodrich; Max Hasin; Lawrence Chan; Luke Harold Miles; Tao R. Lin; Hjalmar Wijk; Joel Burget; Aaron Ho; Elizabeth Barnes; et al. (CoRR, 2023)

Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training. - Evan Hubinger; Carson Denison; Jesse Mu; Mike Lambert; Meg Tong; Monte MacDiarmid; Tamera Lanham; Daniel M. Ziegler; Tim Maxwell; Newton Cheng; Adam S. Jermyn; Amanda Askell; et al. (CoRR, 2024)

Towards a Law of Iterated Expectations for Heuristic Estimators. - Paul F. Christiano; Jacob Hilton; Andrea Lincoln; Eric Neyman; Mark Xu (CoRR, 2024)

International Scientific Report on the Safety of Advanced AI (Interim Report). - Yoshua Bengio; Sören Mindermann; Daniel Privitera; Tamay Besiroglu; Rishi Bommasani; Stephen Casper; Yejin Choi 001; Danielle Goldfarb; Hoda Heidari; Leila Khalatbari; Shayne Longpre; Vasilios Mavroudis; et al. (CoRR, 2024)

Backdoor Defense, Learnability and Obfuscation. - Paul F. Christiano; Jacob Hilton; Victor Lecomte; Mark Xu (ITCS, 2025)