Cover Image

Building Machines that Learn and Think with People

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Collins, Katherine M., Sucholutsky, Ilia, Bhatt, Umang, Chandra, Kartik, Wong, Lionel, Lee, Mina, Zhang, Cedegao E., Zhi-Xuan, Tan, Ho, Mark, Mansinghka, Vikash, Weller, Adrian, Tenenbaum, Joshua B., Griffiths, Thomas L.
Format:	Preprint
Published:	2024
Subjects:	Human-Computer Interaction Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Revisiting Rogers' Paradox in the Context of Human-AI Interaction
by: Collins, Katherine M., et al.
Published: (2025)

Grounding Language about Belief in a Bayesian Theory-of-Mind
by: Ying, Lance, et al.
Published: (2024)

People use fast, goal-directed simulation to reason about novel games
by: Zhang, Cedegao E., et al.
Published: (2024)

Understanding Epistemic Language with a Language-augmented Bayesian Theory of Mind
by: Ying, Lance, et al.
Published: (2024)

On Benchmarking Human-Like Intelligence in Machines
by: Ying, Lance, et al.
Published: (2025)

Pragmatic Instruction Following and Goal Assistance via Cooperative Language-Guided Inverse Planning
by: Zhi-Xuan, Tan, et al.
Published: (2024)

Infinite Ends from Finite Samples: Open-Ended Goal Inference as Top-Down Bayesian Filtering of Bottom-Up Proposals
by: Zhi-Xuan, Tan, et al.
Published: (2024)

People use fast, flat goal-directed simulation to reason about novel problems
by: Collins, Katherine M., et al.
Published: (2025)

Generation and Evaluation in the Human Invention Process through the Lens of Game Design
by: Collins, Katherine M., et al.
Published: (2025)

Empathy in Explanation
by: Collins, Katherine M., et al.
Published: (2025)

Medical Model Synthesis Architectures: A Case Study
by: Collins, Katherine M., et al.
Published: (2026)

Representational Alignment Supports Effective Machine Teaching
by: Sucholutsky, Ilia, et al.
Published: (2024)

Modulating Language Model Experiences through Frictions
by: Collins, Katherine M., et al.
Published: (2024)

When Should We Orchestrate Multiple Agents?
by: Bhatt, Umang, et al.
Published: (2025)

Belief Attribution as Mental Explanation: The Role of Accuracy, Informativity, and Causality
by: Ying, Lance, et al.
Published: (2025)

Language-Informed Synthesis of Rational Agent Models for Grounded Theory-of-Mind Reasoning On-The-Fly
by: Ying, Lance, et al.
Published: (2025)

Large Language Models Assume People are More Rational than We Really are
by: Liu, Ryan, et al.
Published: (2024)

Evaluating Language Models' Evaluations of Games
by: Collins, Katherine M., et al.
Published: (2025)

Language Model Teams as Distributed Systems
by: Mieczkowski, Elizabeth, et al.
Published: (2026)

Self-Steering Language Models
by: Grand, Gabriel, et al.
Published: (2025)

WatChat: Explaining perplexing programs by debugging mental models
by: Chandra, Kartik, et al.
Published: (2024)

Learning Human-like Representations to Enable Learning Human Values
by: Wynn, Andrea, et al.
Published: (2023)

Identifying, Evaluating, and Mitigating Risks of AI Thought Partnerships
by: Oktar, Kerem, et al.
Published: (2025)

Modeling Open-World Cognition as On-Demand Synthesis of Probabilistic Models
by: Wong, Lionel, et al.
Published: (2025)

Learning Personalized Decision Support Policies
by: Bhatt, Umang, et al.
Published: (2023)

Under the Influence: Quantifying Persuasion and Vigilance in Large Language Models
by: Robinson, Sasha, et al.
Published: (2026)

Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness
by: Curtis, Aidan, et al.
Published: (2024)

Why Human Guidance Matters in Collaborative Vibe Coding
by: Hu, Haoyu, et al.
Published: (2026)

The efficiency-gain illusion: People underestimate the rate of AI use and overestimate its benefits on simple tasks
by: Yu, Sunny, et al.
Published: (2026)

Measuring Implicit Bias in Explicitly Unbiased Large Language Models
by: Bai, Xuechunzi, et al.
Published: (2024)

Analyzing the Roles of Language and Vision in Learning from Limited Data
by: Chen, Allison, et al.
Published: (2024)

What is a Number, That a Large Language Model May Know It?
by: Marjieh, Raja, et al.
Published: (2025)

Unequal Uncertainty: Rethinking Algorithmic Interventions for Mitigating Discrimination from AI
by: Sargeant, Holli, et al.
Published: (2025)

Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse
by: Liu, Ryan, et al.
Published: (2024)

GenMatter: Perceiving Physical Objects with Generative Matter Models
by: Li, Eric, et al.
Published: (2026)

Do Large Language Models Mentalize When They Teach?
by: Harootonian, Sevan K., et al.
Published: (2026)

Improving the Efficiency of Language Agent Teams with Adaptive Task Graphs
by: Mieczkowski, Elizabeth, et al.
Published: (2026)

Using LLMs to Advance the Cognitive Science of Collectives
by: Sucholutsky, Ilia, et al.
Published: (2025)

Code-enabled language models can outperform reasoning models on diverse tasks
by: Zhang, Cedegao E., et al.
Published: (2025)

Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesians
by: Chandra, Kartik, et al.
Published: (2026)