64 citations · 123 across the 15 of their papers we have counts for
15 papers
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…
Embedding high-resolution touch across robotic hands enables adaptive human-like grasping
Zihang Zhao, Wanlin Li, Yuyang Li +9
Developing robotic hands that adapt to real-world dynamics remains a fundamental challenge in robotics and machine intelligence. Despite significant advances in replicating human h…
Ag2Manip: Learning Novel Manipulation Skills with Agent-Agnostic Visual and Action Representations
Puhao Li, Tengyu Liu, Yuyang Li +6
Autonomous robotic systems capable of learning novel manipulation tasks are poised to transform industries from manufacturing to service automation. However, modern methods (e.g.,…
PhyRecon: Physically Plausible Neural Scene Reconstruction
Junfeng Ni, Yixin Chen, Bohan Jing +7
We address the issue of physical implausibility in multi-view neural reconstruction. While implicit representations have gained popularity in multi-view 3D reconstruction, previous…
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…
Part-level Scene Reconstruction Affords Robot Interaction
Zeyu Zhang, Lexing Zhang, Zaijin Wang +5
Existing methods for reconstructing interactive scenes primarily focus on replacing reconstructed objects with CAD models retrieved from a limited database, resulting in significan…
Rearrange Indoor Scenes for Human-Robot Co-Activity
Weiqi Wang, Zihang Zhao, Ziyuan Jiao +3
We present an optimization-based framework for rearranging indoor furniture to accommodate human-robot co-activities better. The rearrangement aims to afford sufficient accessible…
Diffusion-based Generation, Optimization, and Planning in 3D Scenes
Siyuan Huang, Zan Wang, Puhao Li +5
We introduce SceneDiffuser, a conditional generative model for 3D scene understanding. SceneDiffuser provides a unified model for solving scene-conditioned generation, optimization…
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…
Neural-Symbolic Recursive Machine for Systematic Generalization
Qing Li, Yixin Zhu, Yitao Liang +3
Current learning models often struggle with human-like systematic generalization, particularly in learning compositional rules from limited data and extrapolating them to novel com…
Sequential Manipulation Planning on Scene Graph
Ziyuan Jiao, Yida Niu, Zeyu Zhang +3
We devise a 3D scene graph representation, contact graph+ (cg+), for efficient sequential task planning. Augmented with predicate-like attributes, this contact graph-based represen…
Understanding Physical Effects for Effective Tool-use
Zeyu Zhang, Ziyuan Jiao, Weiqi Wang +3
We present a robot learning and planning framework that produces an effective tool-use strategy with the least joint efforts, capable of handling objects different from training. L…
Evaluating and Inducing Personality in Pre-trained Language Models
Guangyuan Jiang, Manjie Xu, Song-Chun Zhu +3
Standardized and quantified evaluation of machine behaviors is a crux of understanding LLMs. In this study, we draw inspiration from psychometric studies by leveraging human person…