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Evaluating Models of Robust Word Recognition with Serial Reproduction
Spoken communication occurs in a "noisy channel" characterized by high l...
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Show or Tell? Demonstration is More Robust to Changes in Shared Perception than Explanation
Successful teaching entails a complex interaction between a teacher and ...
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Competition in Cross-situational Word Learning: A Computational Study
Children learn word meanings by tapping into the commonalities across di...
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Investigating representations of verb bias in neural language models
Languages typically provide more than one grammatical construction to ex...
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Meta-Learning of Compositional Task Distributions in Humans and Machines
Modern machine learning systems struggle with sample efficiency and are ...
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Learning Rewards from Linguistic Feedback
We explore unconstrained natural language feedback as a learning signal ...
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Understanding Human Intelligence through Human Limitations
Recent progress in artificial intelligence provides the opportunity to a...
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Resource-rational Task Decomposition to Minimize Planning Costs
People often plan hierarchically. That is, rather than planning over a m...
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End-to-end Deep Prototype and Exemplar Models for Predicting Human Behavior
Traditional models of category learning in psychology focus on represent...
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Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions
This paper seeks to establish a framework for directing a society of sim...
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Universal linguistic inductive biases via meta-learning
How do learners acquire languages from the limited data available to the...
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Analogy as Nonparametric Bayesian Inference over Relational Systems
Much of human learning and inference can be framed within the computatio...
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Extracting low-dimensional psychological representations from convolutional neural networks
Deep neural networks are increasingly being used in cognitive modeling a...
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The Efficiency of Human Cognition Reflects Planned Information Processing
Planning is useful. It lets people take actions that have desirable long...
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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...
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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...
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On the Utility of Learning about Humans for Human-AI Coordination
While we would like agents that can coordinate with humans, current algo...
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Human uncertainty makes classification more robust
The classification performance of deep neural networks has begun to asym...
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The Computational Structure of Unintentional Meaning
Speech-acts can have literal meaning as well as pragmatic meaning, but t...
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Cognitive Model Priors for Predicting Human Decisions
Human decision-making underlies all economic behavior. For the past four...
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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...
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Predicting human decisions with behavioral theories and machine learning
Behavioral decision theories aim to explain human behavior. Can they hel...
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Using Machine Learning to Guide Cognitive Modeling: A Case Study in Moral Reasoning
Large-scale behavioral datasets enable researchers to use complex machin...
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Online gradient-based mixtures for transfer modulation in meta-learning
Learning-to-learn or meta-learning leverages data-driven inductive bias ...
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Multitasking Capacity: Hardness Results and Improved Constructions
We consider the problem of determining the maximal α∈ (0,1] such that ev...
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Evaluating Theory of Mind in Question Answering
We propose a new dataset for evaluating question answering models with r...
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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...
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Representational efficiency outweighs action efficiency in human program induction
The importance of hierarchically structured representations for tractabl...
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Automatically Composing Representation Transformations as a Means for Generalization
How can we build a learner that can capture the essence of what makes a ...
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Learning a face space for experiments on human identity
Generative models of human identity and appearance have broad applicabil...
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Learning Hierarchical Visual Representations in Deep Neural Networks Using Hierarchical Linguistic Labels
Modern convolutional neural networks (CNNs) are able to achieve human-le...
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Capturing human category representations by sampling in deep feature spaces
Understanding how people represent categories is a core problem in cogni...
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Investigating Human Priors for Playing Video Games
What makes humans so good at solving seemingly complex video games? Unli...
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Generating Plans that Predict Themselves
Collaboration requires coordination, and we coordinate by anticipating o...
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Goal Inference Improves Objective and Perceived Performance in Human-Robot Collaboration
The study of human-robot interaction is fundamental to the design and us...
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Learning to select computations
Efficient use of limited computational resources is essential to intelli...
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Modeling Human Categorization of Natural Images Using Deep Feature Representations
Over the last few decades, psychologists have developed sophisticated fo...
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Pragmatic-Pedagogic Value Alignment
For an autonomous system to provide value (e.g., to customers, designers...
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Leveraging deep neural networks to capture psychological representations
Artificial neural networks have seen a recent surge in popularity for th...
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Evaluating vector-space models of analogy
Vector-space representations provide geometric tools for reasoning about...
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A rational analysis of curiosity
We present a rational analysis of curiosity, proposing that people's cur...
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Evidence for the size principle in semantic and perceptual domains
Shepard's Universal Law of Generalization offered a compelling case for ...
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Word forms - not just their lengths- are optimized for efficient communication
The inverse relationship between the length of a word and the frequency ...
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Adapting Deep Network Features to Capture Psychological Representations
Deep neural networks have become increasingly successful at solving clas...
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The nested Chinese restaurant process and Bayesian nonparametric inference of topic hierarchies
We present the nested Chinese restaurant process (nCRP), a stochastic pr...
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