← Authors

Tom Griffiths

21 papers · 2007–2023 · 4 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (16) 🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (8) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (4) πŸ—ΊοΈ Taxonomy Completionist (14) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌱 Topic Pioneer 🧬 Topic Evolution πŸ—ƒοΈ Keyword Collector (107) πŸ“ˆ Trend Setter πŸ’Ž Century Club (21) πŸ”₯ Unstoppable (7)

Conferences

NIPS (14) ICML (4) EMNLP (2) ACL (1)

Top co-authors

Erin Grant (5) Michael Chang (4) Ishita Dasgupta (3) Sergey Levine (3) Mark K Ho (2) Aida Nematzadeh (2) Jonathan D. Cohen (2) Karthik Narasimhan (2) Robert Hawkins (2) Sid Kaushik (2)

Keywords

neural network (4) reinforcement learning (3) few-shot learning (3) transfer learning (2) inductive bia (2) attention mechanism (2) question answering (2) credit assignment (2) multi-agent system (2) representation learning (2) multi-task learning (1) probabilistic modeling (1) network architecture (1) computer vision (1) sample efficiency (1) image classification (1) approximate inference (1) bounded rationality (1) dirichlet process (1) policy gradient (1)

Papers

Tree of Thoughts: Deliberate Problem Solving with Large Language Models NIPS 2023
Alignment with human representations supports robust few-shot learning NIPS 2023
Gaussian Process Probes (GPP) for Uncertainty-Aware Probing NIPS 2023
Im-Promptu: In-Context Composition from Image Prompts NIPS 2023
Distinguishing rule and exemplar-based generalization in learning systems ICML 2022
Using natural language and program abstractions to instill human inductive biases in machines NIPS 2022
Object Representations as Fixed Points: Training Iterative Refinement Algorithms with Implicit Differentiation NIPS 2022
How to talk so AI will learn: Instructions, descriptions, and autonomy NIPS 2022
Passive attention in artificial neural networks predicts human visual selectivity NIPS 2021
Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment ICML 2021
Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions ICML 2020
Reconciling meta-learning and continual learning with online mixtures of tasks NIPS 2019
On the Utility of Learning about Humans for Human-AI Coordination NIPS 2019
Exploiting Attention to Reveal Shortcomings in Memory Models EMNLP 2018
Investigating Human Priors for Playing Video Games ICML 2018
Evaluating Theory of Mind in Question Answering EMNLP 2018
A graph-theoretic approach to multitasking NIPS 2017
Algorithm selection by rational metareasoning as a model of human strategy selection NIPS 2014
Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies NIPS 2013
Burn-in, bias, and the rationality of anchoring NIPS 2012
A fully Bayesian approach to unsupervised part-of-speech tagging ACL 2007