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20242026
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cs.CV2026

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…

cs.CV2026

LocateAnything: Fast and High-Quality Vision-Language Grounding with Parallel Box Decoding

Shihao Wang, Shilong Liu, Yuanguo Kuang +10

Vision-language models (VLMs) commonly formulate visual grounding and detection as a coordinate-token generation problem, serializing each 2D box into multiple 1D tokens that are l…

cs.CV2026

Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning

Chi-Pin Huang, Yunze Man, Zhiding Yu +4

Vision-Language-Action (VLA) tasks require reasoning over complex visual scenes and executing adaptive actions in dynamic environments. While recent studies on reasoning VLAs show…

cs.CV2026

LocateAnything3D: Vision-Language 3D Detection with Chain-of-Sight

Yunze Man, Shihao Wang, Guowen Zhang +7

To act in the world, a model must name what it sees and know where it is in 3D. Today's vision-language models (VLMs) excel at open-ended 2D description and grounding, yet multi-ob…

cs.CV2025

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…

cs.CV2025

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…