4 papers
ChartFI: Benchmarking Faithfulness and Insightfulness of Chart Descriptions from Multimodal Large Language Models
Fen Wang, Zekai Shao, Qiman Kang +5
Chart descriptions are essential for accessibility, cross-modal retrieval, and assisting readers in extracting insights from complex visualizations. As multimodal large language mo…
IMUG-Bench: Benchmarking Unified Multimodal Models on Interleaved Understanding and Generation
Lingyi Meng, Zecong Tang, Haoran Li +12
In recent years, unified multimodal models (UMMs) have emerged to support both understanding and generation within a single framework. Mastering dynamic, multi-turn interleaved ima…
Drive-KD: Multi-Teacher Distillation for VLMs in Autonomous Driving
Weitong Lian, Zecong Tang, Haoran Li +12
Autonomous driving is an important and safety-critical task, and recent advances in LLMs/VLMs have opened new possibilities for reasoning and planning in this domain. However, larg…
Drive-P2D: A Progressive Perception-to-Decision Benchmark for VLMs in Autonomous Driving
Zecong Tang, Zixu Wang, Yifei Wang +10
Autonomous driving requires reliable perception and safe decision-making in complex scenarios. Recent vision-language models (VLMs) demonstrate reasoning and generalization abiliti…