29 citations · 59 across the 14 of their papers we have counts for
9 papers · 1 filter
MemAct: Streaming Spatial Understanding with Memory and Active Exploration
Yuxi Wei, Wei Huang, Qirui Chen +2
Spatial understanding is essential for embodied agents navigating and interacting with the physical world. As observations arrive incrementally, agents must reason in a streaming m…
OmniGameArena: A Unified UE5 Benchmark for VLM Game Agents with Improvement Dynamics
Mingxian Lin, Shengju Qian, Yuqi Liu +9
Vision-language model (VLM) agents are increasingly deployed in interactive game environments. Yet game benchmarks for VLM agents typically report a single first-attempt score per…
SpatialEdit: Benchmarking Fine-Grained Image Spatial Editing
Yicheng Xiao, Wenhu Zhang, Lin Song +10
Image spatial editing performs geometry-driven transformations, allowing precise control over object layout and camera viewpoints. Current models are insufficient for fine-grained…
See, Remember, Explore: A Benchmark and Baselines for Streaming Spatial Reasoning
Yuxi Wei, Wei Huang, Qirui Chen +2
Spatial understanding is fundamental for embodied agents, yet most spatial VLMs and benchmarks remain offline-evaluating post-hoc QA over pre-recorded inputs and overlooking two cr…
Learning to Reason in 4D: Dynamic Spatial Understanding for Vision Language Models
Shengchao Zhou, Yuxin Chen, Yuying Ge +4
Vision-language models (VLM) excel at general understanding yet remain weak at dynamic spatial reasoning (DSR), i.e., reasoning about the evolvement of object geometry and relation…
EmbRACE-3K: Embodied Reasoning and Action in Complex Environments
Mingxian Lin, Wei Huang, Yitang Li +6
Recent advanced vision-language models(VLMs) have demonstrated strong performance on passive, offline image and video understanding tasks. However, their effectiveness in embodied…
2D Instance Editing in 3D Space
Yuhuan Xie, Aoxuan Pan, Ming-Xian Lin +3
Generative models have achieved significant progress in advancing 2D image editing, demonstrating exceptional precision and realism. However, they often struggle with consistency a…
Scaling RL to Long Videos
Yukang Chen, Wei Huang, Baifeng Shi +11
We introduce a full-stack framework that scales up reasoning in vision-language models (VLMs) to long videos, leveraging reinforcement learning. We address the unique challenges of…
VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame Selection
Songhao Han, Wei Huang, Hairong Shi +7
The advancement of Large Vision Language Models (LVLMs) has significantly improved multimodal understanding, yet challenges remain in video reasoning tasks due to the scarcity of h…