SIDS (A Symbolic Interactive Design System). - Dave Clary; Robert Kirk; Steve Sapiro (DAC, 1980)

A timing verification system based on extracted MOS/VLSI circuit parameters. - Pauline Ng; Wolfram Glauert; Robert Kirk (DAC, 1981)

How physicalists can avoid reductionism. - Robert Kirk (Synth., 1996)

Physicalism and strict implication. - Robert Kirk (Synth., 2006)

Insights From the NeurIPS 2021 NetHack Challenge. - Eric Hambro; Sharada P. Mohanty; Dmitrii Babaev; Minwoo Byeon; Dipam Chakraborty; Edward Grefenstette; Minqi Jiang; DaeJin Jo; Anssi Kanervisto; Jongmin Kim 006; Sungwoong Kim; Robert Kirk; et al. (NeurIPS (Competition and Demos), 2021)

MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research. - Mikayel Samvelyan; Robert Kirk; Vitaly Kurin; Jack Parker-Holder; Minqi Jiang; Eric Hambro; Fabio Petroni; Heinrich Küttler; Edward Grefenstette; Tim Rocktäschel (NeurIPS Datasets and Benchmarks, 2021)

A Survey of Generalisation in Deep Reinforcement Learning. - Robert Kirk; Amy Zhang 001; Edward Grefenstette; Tim Rocktäschel (CoRR, 2021)

Graph Backup: Data Efficient Backup Exploiting Markovian Transitions. - Zhengyao Jiang; Tianjun Zhang; Robert Kirk; Tim Rocktäschel; Edward Grefenstette (CoRR, 2022)

Domain Generalization for Robust Model-Based Offline Reinforcement Learning. - Alan Clark; Shoaib Ahmed Siddiqui; Robert Kirk; Usman Anwar; Stephen Chung; David Krueger 001 (CoRR, 2022)

What Mechanisms Does Knowledge Distillation Distill? - Cindy Wu; Ekdeep Singh Lubana; Bruno Kacper Mlodozeniec; Robert Kirk; David Krueger 001 (UniReps, 2023)

Leading the Pack: N-player Opponent Shaping. - Alexandra Souly; Timon Willi; Akbir Khan; Robert Kirk; Chris Lu 001; Edward Grefenstette; Tim Rocktäschel (CoRR, 2023)

A Survey of Zero-shot Generalisation in Deep Reinforcement Learning. - Robert Kirk; Amy Zhang 001; Edward Grefenstette; Tim Rocktäschel (J. Artif. Intell. Res., 2023)

Reward Model Ensembles Help Mitigate Overoptimization. - Thomas Coste; Usman Anwar; Robert Kirk; David Krueger 001 (ICLR, 2024)

Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks. - Samyak Jain; Robert Kirk; Ekdeep Singh Lubana; Robert P. Dick; Hidenori Tanaka; Tim Rocktäschel; Edward Grefenstette; David Scott Krueger (ICLR, 2024)

Understanding the Effects of RLHF on LLM Generalisation and Diversity. - Robert Kirk; Ishita Mediratta; Christoforos Nalmpantis; Jelena Luketina; Eric Hambro; Edward Grefenstette; Roberta Raileanu (ICLR, 2024)

Generalization to New Sequential Decision Making Tasks with In-Context Learning. - Sharath Chandra Raparthy; Eric Hambro; Robert Kirk; Mikael Henaff; Roberta Raileanu (ICML, 2024)

Analysing the Generalisation and Reliability of Steering Vectors. - Daniel Tan; David Chanin; Aengus Lynch; Brooks Paige; Dimitrios Kanoulas; Adrià Garriga-Alonso; Robert Kirk (NeurIPS, 2024)

Analyzing the Generalization and Reliability of Steering Vectors. - Daniel Tan; David Chanin; Aengus Lynch; Dimitrios Kanoulas; Brooks Paige; Adrià Garriga-Alonso; Robert Kirk (CoRR, 2024)

Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models. - Laura Ruis; Maximilian Mozes; Juhan Bae; Siddhartha Rao Kamalakara; Dwarak Talupuru; Acyr Locatelli; Robert Kirk; Tim Rocktäschel; Edward Grefenstette; Max Bartolo (CoRR, 2024)

Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models. - Laura Ruis; Maximilian Mozes; Juhan Bae; Siddhartha Rao Kamalakara; Dwaraknath Gnaneshwar; Acyr Locatelli; Robert Kirk; Tim Rocktäschel; Edward Grefenstette; Max Bartolo (ICLR, 2025)

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities. - Zora Che; Stephen Casper; Robert Kirk; Anirudh Satheesh; Stewart Slocum; Lev E. McKinney; Rohit Gandikota; Aidan Ewart; Domenic Rosati; Zichu Wu; Zikui Cai; Bilal Chughtai; et al. (Trans. Mach. Learn. Res., 2025)

Open Problems in Machine Unlearning for AI Safety. - Fazl Barez; Tingchen Fu; Ameya Prabhu; Stephen Casper; Amartya Sanyal; Adel Bibi; Aidan O'Gara; Robert Kirk; Ben Bucknall; Timothy Fist; Luke Ong; Philip Torr 001; et al. (CoRR, 2025)

Investigating Non-Transitivity in LLM-as-a-Judge. - Yi Xu; Laura Ruis; Tim Rocktäschel; Robert Kirk (CoRR, 2025)

Fundamental Limitations in Defending LLM Finetuning APIs. - Xander Davies; Eric Winsor; Tomek Korbak; Alexandra Souly; Robert Kirk; Christian Schröder de Witt; Yarin Gal (CoRR, 2025)

Dataset Featurization: Uncovering Natural Language Features through Unsupervised Data Reconstruction. - Michal Bravansky; Vaclav Kubon; Suhas Hariharan; Robert Kirk (CoRR, 2025)

How Do Large Language Monkeys Get Their Power (Laws)? - Rylan Schaeffer; Joshua Kazdan; John Hughes; Jordan Juravsky; Sara Price; Aengus Lynch; Erik Jones; Robert Kirk; Azalia Mirhoseini; Sanmi Koyejo (CoRR, 2025)

An Example Safety Case for Safeguards Against Misuse. - Joshua Clymer; Jonah Weinbaum; Robert Kirk; Kimberly Mai; Selena Zhang; Xander Davies (CoRR, 2025)

Reward Model Overoptimisation in Iterated RLHF. - Lorenz Wolf; Robert Kirk; Mirco Musolesi (CoRR, 2025)

Existing Large Language Model Unlearning Evaluations Are Inconclusive. - Zhili Feng; Yixuan Even Xu; Alexander Robey; Robert Kirk; Xander Davies; Yarin Gal; Avi Schwarzschild; J. Zico Kolter (CoRR, 2025)

STACK: Adversarial Attacks on LLM Safeguard Pipelines. - Ian R. McKenzie; Oskar Hollinsworth; Tom Tseng; Xander Davies; Stephen Casper; Aaron D. Tucker; Robert Kirk; Adam Gleave (CoRR, 2025)

Security Challenges in AI Agent Deployment: Insights from a Large Scale Public Competition. - Andy Zou; Maxwell Lin; Eliot Krzysztof Jones; Micha Nowak; Mateusz Dziemian; Nick Winter; Alexander Grattan; Valent Nathanael; Ayla Croft; Xander Davies; Jai Patel; Robert Kirk; 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)