64 citations · 123 across the 15 of their papers we have counts for
5 papers · 1 filter
Grounding Before Generalizing: How AI Differs from Humans in Causal Transfer
Liangru Xiang, Yuxi Ma, Zhihao Cao +2
Extracting abstract causal structures and applying them to novel situations is a hallmark of human intelligence. While Large Language Models (LLMs) and Vision Language Models (VLMs…
Proposing and solving olympiad geometry with guided tree search
Chi Zhang, Jiajun Song, Siyu Li +5
Mathematics olympiads are prestigious competitions, with problem proposing and solving highly honored. Building artificial intelligence that proposes and solves olympiads presents…
X-VoE: Measuring eXplanatory Violation of Expectation in Physical Events
Bo Dai, Linge Wang, Baoxiong Jia +4
Intuitive physics is pivotal for human understanding of the physical world, enabling prediction and interpretation of events even in infancy. Nonetheless, replicating this level of…
ProAgent: Building Proactive Cooperative Agents with Large Language Models
Ceyao Zhang, Kaijie Yang, Siyi Hu +12
Building agents with adaptive behavior in cooperative tasks stands as a paramount goal in the realm of multi-agent systems. Current approaches to developing cooperative agents rely…
On the Complexity of Bayesian Generalization
Yu-Zhe Shi, Manjie Xu, John E. Hopcroft +6
We consider concept generalization at a large scale in the diverse and natural visual spectrum. Established computational modes (i.e., rule-based or similarity-based) are primarily…