Thomas L. Griffiths

research

∙ 08/11/2022

Gaussian process surrogate models for neural networks

The lack of insight into deep learning systems hinders their systematic ...

Michael Y. Li, et al. ∙

research

∙ 07/07/2022

Predicting Word Learning in Children from the Performance of Computer Vision Systems

For human children as well as machine learning systems, a key challenge ...

Sunayana Rane, et al. ∙

research

∙ 07/02/2022

Object Representations as Fixed Points: Training Iterative Refinement Algorithms with Implicit Differentiation

Iterative refinement – start with a random guess, then iteratively impro...

Michael Chang, et al. ∙

research

∙ 06/16/2022

How to talk so your robot will learn: Instructions, descriptions, and pragmatics

From the earliest years of our lives, humans use language to express our...

Theodore R. Sumers, et al. ∙

research

∙ 06/08/2022

Words are all you need? Capturing human sensory similarity with textual descriptors

Recent advances in multimodal training use textual descriptions to signi...

Raja Marjieh, et al. ∙

research

∙ 05/23/2022

Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines

Strong inductive biases are a key component of human intelligence, allow...

Sreejan Kumar, et al. ∙

research

∙ 04/11/2022

Linguistic communication as (inverse) reward design

Natural language is an intuitive and expressive way to communicate rewar...

Theodore R. Sumers, et al. ∙

research

∙ 04/04/2022

Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning

The ability to acquire abstract knowledge is a hallmark of human intelli...

Sreejan Kumar, et al. ∙

research

∙ 02/24/2022

Probing BERT's priors with serial reproduction chains

We can learn as much about language models from what they say as we lear...

Takateru Yamakoshi, et al. ∙

research

∙ 02/09/2022

Predicting Human Similarity Judgments Using Large Language Models

Similarity judgments provide a well-established method for accessing men...

Raja Marjieh, et al. ∙

research

∙ 02/09/2022

Can Humans Do Less-Than-One-Shot Learning?

Being able to learn from small amounts of data is a key characteristic o...

Maya Malaviya, et al. ∙

research

∙ 12/07/2021

A pragmatic account of the weak evidence effect

Language is not only used to inform. We often seek to persuade by arguin...

Samuel A. Barnett, et al. ∙

research

∙ 10/08/2021

Distinguishing rule- and exemplar-based generalization in learning systems

Despite the increasing scale of datasets in machine learning, generaliza...

Ishita Dasgupta, et al. ∙

research

∙ 09/01/2021

Cognitive science as a source of forward and inverse models of human decisions for robotics and control

Those designing autonomous systems that interact with humans will invari...

Mark K Ho, et al. ∙

research

∙ 07/14/2021

Passive attention in artificial neural networks predicts human visual selectivity

Developments in machine learning interpretability techniques over the pa...

Thomas A. Langlois, et al. ∙

research

∙ 06/28/2021

Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment

Many transfer problems require re-using previously optimal decisions for...

Michael Chang, et al. ∙

research

∙ 05/25/2021

Extending rational models of communication from beliefs to actions

Speakers communicate to influence their partner's beliefs and shape thei...

Theodore R. Sumers, et al. ∙

research

∙ 05/15/2021

Are Convolutional Neural Networks or Transformers more like human vision?

Modern machine learning models for computer vision exceed humans in accu...

Shikhar Tuli, et al. ∙

research

∙ 05/14/2021

Control of mental representations in human planning

One of the most striking features of human cognition is the capacity to ...

Mark K Ho, et al. ∙

research

∙ 05/13/2021

Shades of confusion: Lexical uncertainty modulates ad hoc coordination in an interactive communication task

There is substantial variability in the expectations that communication ...

Sonia K. Murthy, et al. ∙

research

∙ 04/12/2021

From partners to populations: A hierarchical Bayesian account of coordination and convention

Languages are powerful solutions to coordination problems: they provide ...

Robert D. Hawkins, et al. ∙

research

∙ 01/24/2021

Evaluating Models of Robust Word Recognition with Serial Reproduction

Spoken communication occurs in a "noisy channel" characterized by high l...

Stephan C. Meylan, et al. ∙

research

∙ 12/16/2020

Show or Tell? Demonstration is More Robust to Changes in Shared Perception than Explanation

Successful teaching entails a complex interaction between a teacher and ...

Theodore R. Sumers, et al. ∙

research

∙ 12/06/2020

Competition in Cross-situational Word Learning: A Computational Study

Children learn word meanings by tapping into the commonalities across di...

Aida Nematzadeh, et al. ∙

research

∙ 10/05/2020

Investigating representations of verb bias in neural language models

Languages typically provide more than one grammatical construction to ex...

Robert D. Hawkins, et al. ∙

research

∙ 10/05/2020

Meta-Learning of Compositional Task Distributions in Humans and Machines

Modern machine learning systems struggle with sample efficiency and are ...

Sreejan Kumar, et al. ∙

research

∙ 09/30/2020

Learning Rewards from Linguistic Feedback

We explore unconstrained natural language feedback as a learning signal ...

Theodore R. Sumers, et al. ∙

research

∙ 09/29/2020

Understanding Human Intelligence through Human Limitations

Recent progress in artificial intelligence provides the opportunity to a...

Thomas L. Griffiths, et al. ∙

research

∙ 07/27/2020

Resource-rational Task Decomposition to Minimize Planning Costs

People often plan hierarchically. That is, rather than planning over a m...

Carlos G. Correa, et al. ∙

research

∙ 07/17/2020

End-to-end Deep Prototype and Exemplar Models for Predicting Human Behavior

Traditional models of category learning in psychology focus on represent...

Pulkit Singh, et al. ∙

research

∙ 07/05/2020

Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions

This paper seeks to establish a framework for directing a society of sim...

Michael Chang, et al. ∙

research

∙ 06/29/2020

Universal linguistic inductive biases via meta-learning

How do learners acquire languages from the limited data available to the...

R. Thomas McCoy, et al. ∙

research

∙ 06/07/2020

Analogy as Nonparametric Bayesian Inference over Relational Systems

Much of human learning and inference can be framed within the computatio...

Ruairidh M. Battleday, et al. ∙

research

∙ 05/29/2020

Extracting low-dimensional psychological representations from convolutional neural networks

Deep neural networks are increasingly being used in cognitive modeling a...

Aditi Jha, et al. ∙

research

∙ 02/13/2020

The Efficiency of Human Cognition Reflects Planned Information Processing

Planning is useful. It lets people take actions that have desirable long...

Mark K Ho, et al. ∙

research

∙ 02/04/2020

Generalizing meanings from partners to populations: Hierarchical inference supports convention formation on networks

A key property of linguistic conventions is that they hold over an entir...

Robert D. Hawkins, et al. ∙

research

∙ 10/16/2019

Scaling up Psychology via Scientific Regret Minimization: A Case Study in Moral Decision-Making

Do large datasets provide value to psychologists? Without a systematic m...

Mayank Agrawal, et al. ∙

research

∙ 10/13/2019

On the Utility of Learning about Humans for Human-AI Coordination

While we would like agents that can coordinate with humans, current algo...

Micah Carroll, et al. ∙

research

∙ 08/19/2019

Human uncertainty makes classification more robust

The classification performance of deep neural networks has begun to asym...

Joshua C. Peterson, et al. ∙

research

∙ 06/03/2019

The Computational Structure of Unintentional Meaning

Speech-acts can have literal meaning as well as pragmatic meaning, but t...

Mark K Ho, et al. ∙

research

∙ 05/22/2019

Cognitive Model Priors for Predicting Human Decisions

Human decision-making underlies all economic behavior. For the past four...

David D. Bourgin, et al. ∙

research

∙ 04/26/2019

Capturing human categorization of natural images at scale by combining deep networks and cognitive models

Human categorization is one of the most important and successful targets...

Ruairidh M. Battleday, et al. ∙

research

∙ 04/15/2019

Predicting human decisions with behavioral theories and machine learning

Behavioral decision theories aim to explain human behavior. Can they hel...

Ori Plonsky, et al. ∙

research

∙ 02/18/2019

Using Machine Learning to Guide Cognitive Modeling: A Case Study in Moral Reasoning

Large-scale behavioral datasets enable researchers to use complex machin...

Mayank Agrawal, et al. ∙

research

∙ 12/14/2018

Online gradient-based mixtures for transfer modulation in meta-learning

Learning-to-learn or meta-learning leverages data-driven inductive bias ...

Ghassen Jerfel, et al. ∙

research

∙ 09/08/2018

Multitasking Capacity: Hardness Results and Improved Constructions

We consider the problem of determining the maximal α∈ (0,1] such that ev...

Noga Alon, et al. ∙

research

∙ 08/28/2018

Evaluating Theory of Mind in Question Answering

We propose a new dataset for evaluating question answering models with r...

Aida Nematzadeh, et al. ∙

research

∙ 08/08/2018

Exploiting Effective Representations for Chinese Sentiment Analysis Using a Multi-Channel Convolutional Neural Network

Effective representation of a text is critical for various natural langu...

Pengfei Liu, et al. ∙

research

∙ 07/18/2018

Representational efficiency outweighs action efficiency in human program induction

The importance of hierarchically structured representations for tractabl...

Sophia Sanborn, et al. ∙

research

∙ 07/12/2018

Automatically Composing Representation Transformations as a Means for Generalization

How can we build a learner that can capture the essence of what makes a ...

Michael B. Chang, et al. ∙

Thomas L. Griffiths

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