12 citations · 19 across the 8 of their papers we have counts for
10 papers
From Macro to Micro: Benchmarking Microscopic Spatial Intelligence on Molecules via Vision-Language Models
Zongzhao Li, Xiangzhe Kong, Jiahui Su +8
This paper introduces the concept of Microscopic Spatial Intelligence (MiSI), the capability to perceive and reason about the spatial relationships of invisible microscopic entitie…
Universally Invariant Learning in Equivariant GNNs
Jiacheng Cen, Anyi Li, Ning Lin +5
Equivariant Graph Neural Networks (GNNs) have demonstrated significant success across various applications. To achieve completeness -- that is, the universal approximation property…
STAR-R1: Spatial TrAnsformation Reasoning by Reinforcing Multimodal LLMs
Zongzhao Li, Zongyang Ma, Mingze Li +6
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities across diverse tasks, yet they lag significantly behind humans in spatial reasoning. We investiga…
Flow Along the K-Amplitude for Generative Modeling
Weitao Du, Shuning Chang, Jiasheng Tang +3
In this work, we propose a novel generative learning paradigm, K-Flow, an algorithm that flows along the -amplitude. Here, is a scaling parameter that organizes frequency ba…
LUCAS: Layered Universal Codec Avatars
Di Liu, Teng Deng, Giljoo Nam +6
Photorealistic 3D head avatar reconstruction faces critical challenges in modeling dynamic face-hair interactions and achieving cross-identity generalization, particularly during e…
Frequency Autoregressive Image Generation with Continuous Tokens
Hu Yu, Hao Luo, Hangjie Yuan +3
Autoregressive (AR) models for image generation typically adopt a two-stage paradigm of vector quantization and raster-scan ``next-token prediction", inspired by its great success…
Large Language-Geometry Model: When LLM meets Equivariance
Zongzhao Li, Jiacheng Cen, Bing Su +4
Accurately predicting 3D structures and dynamics of physical systems is crucial in scientific applications. Existing approaches that rely on geometric Graph Neural Networks (GNNs)…
GenCA: A Text-conditioned Generative Model for Realistic and Drivable Codec Avatars
Keqiang Sun, Amin Jourabloo, Riddhish Bhalodia +9
Photo-realistic and controllable 3D avatars are crucial for various applications such as virtual and mixed reality (VR/MR), telepresence, gaming, and film production. Traditional m…
Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics
Liming Wu, Zhichao Hou, Jirui Yuan +2
Learning to represent and simulate the dynamics of physical systems is a crucial yet challenging task. Existing equivariant Graph Neural Network (GNN) based methods have encapsulat…
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications
Jiaqi Han, Jiacheng Cen, Liming Wu +13
Geometric graphs are a special kind of graph with geometric features, which are vital to model many scientific problems. Unlike generic graphs, geometric graphs often exhibit physi…