3 citations · 9 across the 12 of their papers we have counts for
5 papers · 1 filter
Video-LMM Post-Training: A Deep Dive into Video Reasoning with Large Multimodal Models
Yolo Y. Tang, Jing Bi, Pinxin Liu +24
Video understanding represents the most challenging frontier in computer vision, requiring models to reason about complex spatiotemporal relationships, long-term dependencies, and…
MetaFind: Scene-Aware 3D Asset Retrieval for Coherent Metaverse Scene Generation
Zhenyu Pan, Yucheng Lu, Han Liu
We present MetaFind, a scene-aware tri-modal compositional retrieval framework designed to enhance scene generation in the metaverse by retrieving 3D assets from large-scale reposi…
SciSciGPT: Advancing Human-AI Collaboration in the Science of Science
Erzhuo Shao, Yifang Wang, Yifan Qian +3
The increasing availability of large-scale datasets has fueled rapid progress across many scientific fields, creating unprecedented opportunities for research and discovery while p…
MetaSpatial: Reinforcing 3D Spatial Reasoning in VLMs for the Metaverse
Zhenyu Pan, Han Liu
We present MetaSpatial, the first reinforcement learning (RL)-based framework designed to enhance 3D spatial reasoning in vision-language models (VLMs), enabling real-time 3D scene…
Do Code LLMs Understand Design Patterns?
Zhenyu Pan, Xuefeng Song, Yunkun Wang +4
Code Large Language Models (LLMs) demonstrate great versatility in adapting to various downstream tasks, including code generation and completion, as well as bug detection and fixi…