5 papers
World-in-World: World Models in a Closed-Loop World
Jiahan Zhang, Muqing Jiang, Nanru Dai +14
Generative world models (WMs) can now simulate worlds with striking visual realism, which naturally raises the question of whether they can endow embodied agents with predictive pe…
Generative World Explorer
Taiming Lu, Tianmin Shu, Alan Yuille +2
Planning with partial observation is a central challenge in embodied AI. A majority of prior works have tackled this challenge by developing agents that physically explore their en…
Prompt-Based Exemplar Super-Compression and Regeneration for Class-Incremental Learning
Ruxiao Duan, Jieneng Chen, Adam Kortylewski +2
Replay-based methods in class-incremental learning (CIL) have attained remarkable success. Despite their effectiveness, the inherent memory restriction results in saving a limited…
SpatialLLM: A Compound 3D-Informed Design towards Spatially-Intelligent Large Multimodal Models
Wufei Ma, Luoxin Ye, Celso M de Melo +2
Humans naturally understand 3D spatial relationships, enabling complex reasoning like predicting collisions of vehicles from different directions. Current large multimodal models (…
Spatial457: A Diagnostic Benchmark for 6D Spatial Reasoning of Large Multimodal Models
Xingrui Wang, Wufei Ma, Tiezheng Zhang +3
Although large multimodal models (LMMs) have demonstrated remarkable capabilities in visual scene interpretation and reasoning, their capacity for complex and precise 3-dimensional…