2 papers
cs.CV2026
AgentVista: Evaluating Multimodal Agents in Ultra-Challenging Realistic Visual Scenarios
Zhaochen Su, Jincheng Gao, Hangyu Guo +10
Real-world multimodal agents solve multi-step workflows grounded in visual evidence. For example, an agent can troubleshoot a device by linking a wiring photo to a schematic and va…
cs.CV2024
MLLM-SUL: Multimodal Large Language Model for Semantic Scene Understanding and Localization in Traffic Scenarios
Jiaqi Fan, Jianhua Wu, Jincheng Gao +4
Multimodal large language models (MLLMs) have shown satisfactory effects in many autonomous driving tasks. In this paper, MLLMs are utilized to solve joint semantic scene understan…