activity
20012025
most citedThe large-scale structure of semantic networks: statistical analyses and a model for semantic growth

92 citations · 115 across the 5 of their papers we have counts for

collaborators

5 papers

cs.MA2025

Adaptive Social Learning using Theory of Mind

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 don't always choose to observe others, since social learning can car…

cs.LG2024

Functional Risk Minimization

Ferran Alet, Clement Gehring, Tomás Lozano-Pérez +3

The field of Machine Learning has changed significantly since the 1970s. However, its most basic principle, Empirical Risk Minimization (ERM), remains unchanged. We propose Functio…

cs.RO2024★ 1 cited

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…

cs.AI2024★ 22 cited

STAR: A Benchmark for Situated Reasoning in Real-World Videos

Bo Wu, Shoubin Yu, Zhenfang Chen +2

Reasoning in the real world is not divorced from situations. How to capture the present knowledge from surrounding situations and perform reasoning accordingly is crucial and chall…

cond-mat.soft2001★ 92 cited

The large-scale structure of semantic networks: statistical analyses and a model for semantic growth

Mark Steyvers, Joshua B. Tenenbaum

We present statistical analyses of the large-scale structure of three types of semantic networks: word associations, WordNet, and Roget's thesaurus. We show that they have a small-…