9 papers
PPTArena: A Benchmark for PowerPoint Editing
Michael Ofengenden, Yunze Man, Ziqi Pang +2
We introduce PPTArena, a benchmark for PowerPoint editing that evaluates how agents modify real slides from natural-language instructions. Unlike benchmarks that rely on image-PDF…
One Token per Highly Selective Frame: Towards Extreme Compression for Long Video Understanding
Zheyu Zhang, Ziqi Pang, Shixing Chen +3
Long video understanding is inherently challenging for vision-language models (VLMs) because of the extensive number of frames. With each video frame typically expanding into tens…
OSGym: Scalable OS Infra for Computer Use Agents
Zengyi Qin, Jinyuan Chen, Yunze Man +25
Training computer use agents requires full-featured OS sandboxes with GUI environments, which consume substantial hardware resources as the number of sandboxes scales. Stochastic e…
AgMMU: A Comprehensive Agricultural Multimodal Understanding Benchmark
Aruna Gauba, Irene Pi, Yunze Man +3
We present AgMMU, a challenging real-world benchmark for evaluating and advancing vision-language models (VLMs) in the knowledge-intensive domain of agriculture. Unlike prior datas…
RandAR: Decoder-only Autoregressive Visual Generation in Random Orders
Ziqi Pang, Tianyuan Zhang, Fujun Luan +5
We introduce RandAR, a decoder-only visual autoregressive (AR) model capable of generating images in arbitrary token orders. Unlike previous decoder-only AR models that rely on a p…
MR. Video: "MapReduce" is the Principle for Long Video Understanding
Ziqi Pang, Yu-Xiong Wang
We propose MR. Video, an agentic long video understanding framework that demonstrates the simple yet effective MapReduce principle for processing long videos: (1) Map: independentl…