activity
20212026
most citedThe Neuro-Symbolic Inverse Planning Engine (NIPE): Modeling Probabilistic Social Inferences from Linguistic Inputs

4 citations · 19 across the 24 of their papers we have counts for

collaborators
Showing 2026Show all

7 papers · 1 filter

cs.AI2026

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…

cs.LG2026

PlayTrain: An Efficient Reinforcement Learning Framework for LLM-Generated Adaptable JavaScript Games

Ryan Truong, Lance Ying, Samuel J. Gershman +1

While many video-game environments (VGEs) have played crucial roles in advancing reinforcement learning (RL), developing novel VGEs or modifying existing ones to support new featur…

cs.MA2026

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…

cs.HC2026

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…

cs.CL2026

Post-training makes large language models less human-like

Marcel Binz, Elif Akata, Abdullah Almaatouq +76

Large language models (LLMs) are increasingly used as surrogates for human participants, but it remains unclear which models best capture human behavior and why. To address this, w…

q-bio.NC2026★ 1 cited

Grounding Social Perception in Intuitive Physics

Lance Ying, Aydan Y. Huang, Aviv Netanyahu +4

People infer rich social information from others' actions. These inferences are often constrained by the physical world: what agents can do, what obstacles permit, and how the phys…

cs.AI2026★ 1 cited

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…