91 citations · 127 across the 24 of their papers we have counts for
26 papers
CogGym: Towards Large-Scale Comparative Evaluation of Human and Machine Cognition
Lance Ying, Jinzhou Wu, Yingshan Susan Wang +53
Understanding and modeling human intelligence are parallel goals shared by artificial intelligence (AI) and cognitive science. As AI systems grow increasingly capable, in what ways…
Using Theory of Mind to Arbitrate between Social and Non-social Learning
Lance Ying, Ryan Truong, Joshua B. Tenenbaum +1
Social learning is a powerful mechanism through which agents learn about the world from others. However, humans sometimes choose direct experience over social learning, which can c…
Pragmatic Reasoning in Design
Lance Ying, William Van Uitert, Tan Zhi-Xuan +2
People can often understand and use novel artifacts after only a few interactions, suggesting that design choices communicate underlying affordances and causal structure. We propos…
Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesians
Kartik Chandra, Max Kleiman-Weiner, Jonathan Ragan-Kelley +1
"AI psychosis" or "delusional spiraling" is an emerging phenomenon where AI chatbot users find themselves dangerously confident in outlandish beliefs after extended chatbot convers…
AI Gamestore: Scalable, Open-Ended Evaluation of Machine General Intelligence with Human Games
Lance Ying, Ryan Truong, Prafull Sharma +9
Rigorously evaluating machine intelligence against the broad spectrum of human general intelligence has become increasingly important and challenging in this era of rapid technolog…
Assessing Adaptive World Models in Machines with Novel Games
Lance Ying, Katherine M. Collins, Prafull Sharma +11
Human intelligence exhibits a remarkable capacity for rapid adaptation and effective problem-solving in novel and unfamiliar contexts. We argue that this profound adaptability is f…
Language-Informed Synthesis of Rational Agent Models for Grounded Theory-of-Mind Reasoning On-The-Fly
Lance Ying, Ryan Truong, Katherine M. Collins +6
Drawing real world social inferences usually requires taking into account information from multiple modalities. Language is a particularly powerful source of information in social…
What's in the Box? Reasoning about Unseen Objects from Multimodal Cues
Lance Ying, Daniel Xu, Alicia Zhang +3
People regularly make inferences about objects in the world that they cannot see by flexibly integrating information from multiple sources: auditory and visual cues, language, and…
Empathy in Explanation
Katherine M. Collins, Kartik Chandra, Adrian Weller +2
Why do we give the explanations we do? Recent work has suggested that we should think of explanation as a kind of cooperative social interaction, between a why-question-asker and a…
Resource Rational Contractualism Should Guide AI Alignment
Sydney Levine, Matija Franklin, Tan Zhi-Xuan +8
AI systems will soon have to navigate human environments and make decisions that affect people and other AI agents whose goals and values diverge. Contractualist alignment proposes…
Belief Attribution as Mental Explanation: The Role of Accuracy, Informativity, and Causality
Lance Ying, Almog Hillel, Ryan Truong +3
A key feature of human theory-of-mind is the ability to attribute beliefs to other agents as mentalistic explanations for their behavior. But given the wide variety of beliefs that…
On Benchmarking Human-Like Intelligence in Machines
Lance Ying, Katherine M. Collins, Lionel Wong +6
Recent advances in Artificial Intelligence (AI) have yielded powerful computational models that, by learning from vast amounts of human-generated data, are increasingly posited as…
Hypothesis-Driven Theory-of-Mind Reasoning for Large Language Models
Hyunwoo Kim, Melanie Sclar, Tan Zhi-Xuan +5
Existing LLM reasoning methods have shown impressive capabilities across various tasks, such as solving math and coding problems. However, applying these methods to scenarios witho…
Sketching With Your Voice: "Non-Phonorealistic" Rendering of Sounds via Vocal Imitation
Matthew Caren, Kartik Chandra, Joshua B. Tenenbaum +2
We present a method for automatically producing human-like vocal imitations of sounds: the equivalent of "sketching," but for auditory rather than visual representation. Starting w…
Pragmatic Embodied Spoken Instruction Following in Human-Robot Collaboration with Theory of Mind
Lance Ying, Xinyi Li, Shivam Aarya +6
Spoken language instructions are ubiquitous in agent collaboration. However, in real-world human-robot collaboration, following human spoken instructions can be challenging due to…
Understanding Epistemic Language with a Language-augmented Bayesian Theory of Mind
Lance Ying, Tan Zhi-Xuan, Lionel Wong +2
How do people understand and evaluate claims about others' beliefs, even though these beliefs cannot be directly observed? In this paper, we introduce a cognitive model of epistemi…
Infinite Ends from Finite Samples: Open-Ended Goal Inference as Top-Down Bayesian Filtering of Bottom-Up Proposals
Tan Zhi-Xuan, Gloria Kang, Vikash Mansinghka +1
The space of human goals is tremendously vast; and yet, from just a few moments of watching a scene or reading a story, we seem to spontaneously infer a range of plausible motivati…
Building Machines that Learn and Think with People
Katherine M. Collins, Ilia Sucholutsky, Umang Bhatt +10
What do we want from machine intelligence? We envision machines that are not just tools for thought, but partners in thought: reasonable, insightful, knowledgeable, reliable, and t…
Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems
David "davidad" Dalrymple, Joar Skalse, Yoshua Bengio +14
Ensuring that AI systems reliably and robustly avoid harmful or dangerous behaviours is a crucial challenge, especially for AI systems with a high degree of autonomy and general in…
GOMA: Proactive Embodied Cooperative Communication via Goal-Oriented Mental Alignment
Lance Ying, Kunal Jha, Shivam Aarya +3
Verbal communication plays a crucial role in human cooperation, particularly when the partners only have incomplete information about the task, environment, and each other's mental…
Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness
Aidan Curtis, George Matheos, Nishad Gothoskar +4
Integrated task and motion planning (TAMP) has proven to be a valuable approach to generalizable long-horizon robotic manipulation and navigation problems. However, the typical TAM…
WatChat: Explaining perplexing programs by debugging mental models
Kartik Chandra, Katherine M. Collins, Will Crichton +6
Often, a good explanation for a program's unexpected behavior is a bug in the programmer's code. But sometimes, an even better explanation is a bug in the programmer's mental model…
Pragmatic Instruction Following and Goal Assistance via Cooperative Language-Guided Inverse Planning
Tan Zhi-Xuan, Lance Ying, Vikash Mansinghka +1
People often give instructions whose meaning is ambiguous without further context, expecting that their actions or goals will disambiguate their intentions. How can we build assist…
Grounding Language about Belief in a Bayesian Theory-of-Mind
Lance Ying, Tan Zhi-Xuan, Lionel Wong +2
Despite the fact that beliefs are mental states that cannot be directly observed, humans talk about each others' beliefs on a regular basis, often using rich compositional language…