12 papers
ARIA: A Causal-Aware Framework for Rescuing LLM Reasoning in Trustworthy Materials Discovery
Yi Cao, Liaoyaqi Wang, Jieneng Chen +3
Generative models have revolutionized the process of materials discovery, yet they often fail to satisfy underlying physical causality. Through an analysis of Large Language Models…
3D-Belief: Embodied Belief Inference via Generative 3D World Modeling
Yifan Yin, Zehao Wen, Suyu Ye +10
Recent advances in visual generative models have highlighted the promise of learning generative world models. However, most existing approaches frame world modeling as novel-view s…
GENFIG1: Visual Summaries of Scholarly Work as a Challenge for Vision-Language Models
Yaohan Guan, Pristina Wang, Najim Dehak +3
In many science papers, "Figure 1" serves as the primary visual summary of the core research idea. These figures are visually simple yet conceptually rich, often requiring signific…
Thinking with Spatial Code for Physical-World Video Reasoning
Jieneng Chen, Wenxin Ma, Ruisheng Yuan +3
We introduce Thinking with Spatial Code, a framework that transforms RGB video into explicit, temporally coherent 3D representations for physical-world visual question answering. W…
CausalSpatial: A Benchmark for Object-Centric Causal Spatial Reasoning
Wenxin Ma, Chenlong Wang, Ruisheng Yuan +6
Humans can look at a static scene and instantly predict what happens next -- will moving this object cause a collision? We call this ability Causal Spatial Reasoning. However, curr…
EvoWorld: Evolving Panoramic World Generation with Explicit 3D Memory
Jiahao Wang, Luoxin Ye, TaiMing Lu +8
Humans possess a remarkable ability to mentally explore and replay 3D environments they have previously experienced. Inspired by this mental process, we present EvoWorld: a world m…