Solving Kalah. - Geoffrey Irving; Jeroen Donkers; Jos Uiterwijk (J. Int. Comput. Games Assoc., 2000)

Invertible finite elements for robust simulation of large deformation. - Geoffrey Irving; Joseph Teran; Ronald Fedkiw (Symposium on Computer Animation, 2004)

Robust quasistatic finite elements and flesh simulation. - Joseph Teran; Eftychios Sifakis; Geoffrey Irving; Ronald Fedkiw (Symposium on Computer Animation, 2005)

Tetrahedral and hexahedral invertible finite elements. - Geoffrey Irving; Joseph Teran; Ronald Fedkiw (Graph. Model., 2006)

Efficient simulation of large bodies of water by coupling two and three dimensional techniques. - Geoffrey Irving; Eran Guendelman; Frank Losasso; Ronald Fedkiw (ACM Trans. Graph., 2006)

Melting and Burning Solids into Liquids and Gases. - Frank Losasso; Geoffrey Irving; Eran Guendelman; Ronald Fedkiw (IEEE Trans. Vis. Comput. Graph., 2006)

Hybrid simulation of deformable solids. - Eftychios Sifakis; Tamar Shinar; Geoffrey Irving; Ronald Fedkiw (Symposium on Computer Animation, 2007)

Volume conserving finite element simulations of deformable models. - Geoffrey Irving; Craig A. Schroeder; Ronald Fedkiw (ACM Trans. Graph., 2007)

Methods for the physically based simulation of solids and fluids. - Geoffrey Irving (2007)

Simulating the devolved: finite elements on WALL·E. - Geoffrey Irving; Ryan Kautzman; Gordon Cameron; Jiayi Chong (SIGGRAPH Talks, 2008)

Robust High-Resolution Cloth Using Parallelism, History-Based Collisions, and Accurate Friction. - Andrew Selle; Jonathan Su; Geoffrey Irving; Ronald Fedkiw (IEEE Trans. Vis. Comput. Graph., 2009)

Banded Householder representation of linear subspaces - Geoffrey Irving (CoRR, 2011)

Compression and direct manipulation of complex blendshape models. - Jaewoo Seo; Geoffrey Irving; John P. Lewis; Junyong Noh (ACM Trans. Graph., 2011)

A quantized-diffusion model for rendering translucent materials. - Eugene d'Eon; Geoffrey Irving (ACM Trans. Graph., 2011)

A deterministic pseudorandom perturbation scheme for arbitrary polynomial predicates. - Geoffrey Irving; Forrest Green (CoRR, 2013)

Pentago is a First Player Win: Strongly Solving a Game Using Parallel In-Core Retrograde Analysis. - Geoffrey Irving (CoRR, 2014)

DeepMath - Deep Sequence Models for Premise Selection. - Geoffrey Irving; Christian Szegedy; Alexander A. Alemi; Niklas Eén; François Chollet; Josef Urban (NIPS, 2016)

TensorFlow: A System for Large-Scale Machine Learning. - Martín Abadi; Paul Barham 001; Jianmin Chen; Zhifeng Chen; Andy Davis; Jeffrey Dean; Matthieu Devin; Sanjay Ghemawat; Geoffrey Irving; Michael Isard; Manjunath Kudlur; Josh Levenberg; et al. (OSDI, 2016)

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. - Martín Abadi; Ashish Agarwal; Paul Barham 001; Eugene Brevdo; Zhifeng Chen; Craig Citro; Gregory S. Corrado; Andy Davis; Jeffrey Dean; Matthieu Devin; Sanjay Ghemawat; Ian J. Goodfellow; et al. (CoRR, 2016)

TensorFlow: A system for large-scale machine learning. - Martín Abadi; Paul Barham 001; Jianmin Chen; Zhifeng Chen; Andy Davis; Jeffrey Dean; Matthieu Devin; Sanjay Ghemawat; Geoffrey Irving; Michael Isard; Manjunath Kudlur; Josh Levenberg; et al. (CoRR, 2016)

DeepMath - Deep Sequence Models for Premise Selection. - Alexander A. Alemi; François Chollet; Geoffrey Irving; Christian Szegedy; Josef Urban (CoRR, 2016)

Deep Network Guided Proof Search. - Sarah M. Loos; Geoffrey Irving; Christian Szegedy; Cezary Kaliszyk (LPAR, 2017)

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

AI safety via debate. - Geoffrey Irving; Paul F. Christiano; 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)

Alignment of Language Agents. - Zachary Kenton; Tom Everitt; Laura Weidinger; Iason Gabriel; Vladimir Mikulik; Geoffrey Irving (CoRR, 2021)

Ethical and social risks of harm from Language Models. - Laura Weidinger; John Mellor; Maribeth Rauh; Conor Griffin; Jonathan Uesato; Po-Sen Huang; Myra Cheng; Mia Glaese; Borja Balle; Atoosa Kasirzadeh; Zac Kenton; Sasha Brown; et al. (CoRR, 2021)

Scaling Language Models: Methods, Analysis & Insights from Training Gopher. - Jack W. Rae; Sebastian Borgeaud; Trevor Cai; Katie Millican; Jordan Hoffmann; H. Francis Song; John Aslanides; Sarah Henderson; Roman Ring; Susannah Young; Eliza Rutherford; Tom Hennigan; et al. (CoRR, 2021)

Red Teaming Language Models with Language Models. - Ethan Perez; Saffron Huang; H. Francis Song; Trevor Cai; Roman Ring; John Aslanides; Amelia Glaese; Nat McAleese; Geoffrey Irving (EMNLP, 2022)

Taxonomy of Risks posed by Language Models. - Laura Weidinger; Jonathan Uesato; Maribeth Rauh; Conor Griffin; Po-Sen Huang; John Mellor; Amelia Glaese; Myra Cheng; Borja Balle; Atoosa Kasirzadeh; Courtney Biles; Sasha Brown; et al. (FAccT, 2022)

Improving Language Models by Retrieving from Trillions of Tokens. - Sebastian Borgeaud; Arthur Mensch; Jordan Hoffmann; Trevor Cai; Eliza Rutherford; Katie Millican; George van den Driessche 002; Jean-Baptiste Lespiau; Bogdan Damoc; Aidan Clark; Diego de Las Casas; Aurelia Guy; et al. (ICML, 2022)

Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Models. - Maribeth Rauh; John Mellor; Jonathan Uesato; Po-Sen Huang; Johannes Welbl; Laura Weidinger; Sumanth Dathathri; Amelia Glaese; Geoffrey Irving; Iason Gabriel; William Isaac 001; Lisa Anne Hendricks (NeurIPS, 2022)

Uncertainty Estimation for Language Reward Models. - Adam Gleave; Geoffrey Irving (CoRR, 2022)

Teaching language models to support answers with verified quotes. - Jacob Menick; Maja Trebacz; Vladimir Mikulik; John Aslanides; H. Francis Song; Martin J. Chadwick; Mia Glaese; Susannah Young; Lucy Campbell-Gillingham; Geoffrey Irving; Nat McAleese (CoRR, 2022)

Improving alignment of dialogue agents via targeted human judgements. - Amelia Glaese; Nat McAleese; Maja Trebacz; John Aslanides; Vlad Firoiu; Timo Ewalds; Maribeth Rauh; Laura Weidinger; Martin J. Chadwick; Phoebe Thacker; Lucy Campbell-Gillingham; Jonathan Uesato; et al. (CoRR, 2022)

Fine-Tuning Language Models via Epistemic Neural Networks. - Ian Osband; Seyed Mohammad Asghari; Benjamin Van Roy; Nat McAleese; John Aslanides; Geoffrey Irving (CoRR, 2022)

Solving math word problems with process- and outcome-based feedback. - Jonathan Uesato; Nate Kushman; Ramana Kumar; H. Francis Song; Noah Y. Siegel; Lisa Wang; Antonia Creswell; Geoffrey Irving; Irina Higgins (CoRR, 2022)

Accelerating Large Language Model Decoding with Speculative Sampling. - Charlie Chen; Sebastian Borgeaud; Geoffrey Irving; Jean-Baptiste Lespiau; Laurent Sifre; John Jumper (CoRR, 2023)

Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla. - Tom Lieberum; Matthew Rahtz; János Kramár; Neel Nanda; Geoffrey Irving; Rohin Shah; Vladimir Mikulik (CoRR, 2023)

Scalable AI Safety via Doubly-Efficient Debate. - Jonah Brown-Cohen; Geoffrey Irving; Georgios Piliouras (ICML, 2024)

Safety case template for frontier AI: A cyber inability argument. - Arthur Goemans; Marie Davidsen Buhl; Jonas Schuett; Tomek Korbak; Jessica Wang; Benjamin Hilton; Geoffrey Irving (CoRR, 2024)

A sketch of an AI control safety case. - Tomek Korbak; Joshua Clymer; Benjamin Hilton; Buck Shlegeris; Geoffrey Irving (CoRR, 2025)

Safety Cases: A Scalable Approach to Frontier AI Safety. - Benjamin Hilton; Marie Davidsen Buhl; Tomek Korbak; Geoffrey Irving (CoRR, 2025)

How to evaluate control measures for LLM agents? A trajectory from today to superintelligence. - Tomek Korbak; Mikita Balesni; Buck Shlegeris; Geoffrey Irving (CoRR, 2025)

An alignment safety case sketch based on debate. - Marie Davidsen Buhl; Jacob Pfau; Benjamin Hilton; Geoffrey Irving (CoRR, 2025)

Avoiding Obfuscation with Prover-Estimator Debate. - Jonah Brown-Cohen; Geoffrey Irving; Georgios Piliouras (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)

Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs. - Kyle O'Brien; Stephen Casper; Quentin Anthony; Tomek Korbak; Robert Kirk; Xander Davies; Ishan Mishra; Geoffrey Irving; Yarin Gal; Stella Biderman (CoRR, 2025)