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Stuart Russell

52 papers · 2008–2025 · 10 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (23) 🐝 Cross-Pollinator (12) 🧭 Keyword Pioneer 🌍 Conference Polyglot (10) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (9) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (17) 🌟 Keyword Trendsetter Combo (7) πŸ† Keyword Champion (2) πŸ‘‘ Triple Crown 🧬 Topic Evolution 🀝 Dynamic Duo (11) πŸ† Grand Slam ❓ The Questioner (3) πŸ—ƒοΈ Keyword Collector (57) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (13) πŸš€ Conference Pioneer ⚑ Prolific Year (10) πŸ’Ž Century Club (52)

Conferences

ICML (14) NIPS (13) ICLR (10) IJCAI (5) AISTATS (4) AAAI (2) CORL (1) EMNLP (1) ICCV (1) UAI (1)

Top co-authors

Anca Dragan (11) Dylan Hadfield-Menell (6) Yi Wu (6) Scott Emmons (6) Pieter Abbeel (5) Adam Gleave (4) Hanlin Zhu (4) Michael D Dennis (4) Vincent Conitzer (3) Lei Li (3)

Keywords

bayesian inference (6) game theory (4) multi-agent system (4) partial observability (3) reward function (3) time series (3) generative model (2) representation learning (2) utility function (2) event detection (2) importance sampling (2) posterior inference (2) gaussian process (2) reward learning (2) adversarial training (2) approximate inference (2) human-robot interaction (2) markov chain monte carlo (2) inverse reinforcement learning (2) probabilistic programming (2)

Papers

Monitoring Latent World States in Language Models with Propositional Probes ICLR 2025
Extractive Structures Learned in Pretraining Enable Generalization on Finetuned Facts ICML 2025
Observation Interference in Partially Observable Assistance Games ICML 2025
RL, but don’t do anything I wouldn’t do UAI 2025
Avoiding Catastrophe in Online Learning by Asking for Help ICML 2025
AssistanceZero: Scalably Solving Assistance Games ICML 2025
The Partially Observable Off-Switch Game AAAI 2025
BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping ICLR 2025
Diffusion On Syntax Trees For Program Synthesis ICLR 2025
The Effective Horizon Explains Deep RL Performance in Stochastic Environments ICLR 2024
Evidence of Learned Look-Ahead in a Chess-Playing Neural Network NIPS 2024
Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics NIPS 2024
When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback NIPS 2024
Trajectory Improvement and Reward Learning from Comparative Language Feedback CORL 2024
Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game ICLR 2024
AI Alignment with Changing and Influenceable Reward Functions ICML 2024
Image Hijacks: Adversarial Images can Control Generative Models at Runtime ICML 2024
Position: Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback ICML 2024
On Representation Complexity of Model-based and Model-free Reinforcement Learning ICLR 2024
SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals AISTATS 2023
Invariance in Policy Optimisation and Partial Identifiability in Reward Learning ICML 2023
Who Needs to Know? Minimal Knowledge for Optimal Coordination ICML 2023
Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian ICLR 2023
Adversarial Policies Beat Superhuman Go AIs ICML 2023
For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria ICML 2022
Estimating and Penalizing Induced Preference Shifts in Recommender Systems ICML 2022
Cross-Domain Imitation Learning via Optimal Transport ICLR 2022
Quantifying Differences in Reward Functions ICLR 2021
Adversarial Policies: Attacking Deep Reinforcement Learning ICLR 2020
Bayesian Relational Memory for Semantic Visual Navigation ICCV 2019
Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient AAAI 2019
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning ICML 2018
Learning Plannable Representations with Causal InfoGAN NIPS 2018
Meta-Learning MCMC Proposals NIPS 2018
Negotiable Reinforcement Learning for Pareto Optimal Sequential Decision-Making NIPS 2018
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms ICML 2018
Efficient Reinforcement Learning with Hierarchies of Machines by Leveraging Internal Transitions IJCAI 2017
Should Robots be Obedient? IJCAI 2017
Signal-based Bayesian Seismic Monitoring AISTATS 2017
Adversarial Training for Relation Extraction EMNLP 2017
Inverse Reward Design NIPS 2017
The Off-Switch Game IJCAI 2017
Markovian State and Action Abstractions for MDPs via Hierarchical MCTS IJCAI 2016
Swift: Compiled Inference for Probabilistic Programming Languages IJCAI 2016
Cooperative Inverse Reinforcement Learning NIPS 2016
Gaussian Process Random Fields NIPS 2015
Algorithm selection by rational metareasoning as a model of human strategy selection NIPS 2014
Multilinear Dynamical Systems for Tensor Time Series NIPS 2013
Dynamic Scaled Sampling for Deterministic Constraints AISTATS 2013
Global seismic monitoring as probabilistic inference NIPS 2010
Why are DBNs sparse? AISTATS 2010
Probabilistic detection of short events, with application to critical care monitoring NIPS 2008