3 papers
cs.CV2026
OddGridBench: Exposing the Lack of Fine-Grained Visual Discrepancy Sensitivity in Multimodal Large Language Models
Tengjin Weng, Wenhao Jiang, Jingyi Wang +3
Multimodal large language models (MLLMs) have achieved remarkable performance across a wide range of vision language tasks. However, their ability in low-level visual perception, p…
cs.AI2026
BEAP-Agent: Backtrackable Execution and Adaptive Planning for GUI Agents
Ziyu Lu, Tengjin Weng, Yiying Yang +3
GUI agents are designed to automate repetitive tasks and enhance productivity. However, existing GUI agents struggle to recover once they follow an incorrect exploration path, ofte…
cs.CV2025
VisNumBench: Evaluating Number Sense of Multimodal Large Language Models
Tengjin Weng, Jingyi Wang, Wenhao Jiang +1
Can Multimodal Large Language Models (MLLMs) develop an intuitive number sense similar to humans? Targeting this problem, we introduce Visual Number Benchmark (VisNumBench) to eval…