3 papers
cs.CV2026
Bee: A High-Quality Corpus and Full-Stack Suite to Unlock Advanced Fully Open MLLMs
Yi Zhang, Bolin Ni, Xin-Sheng Chen +7
Fully open multimodal large language models (MLLMs) currently lag behind proprietary counterparts, primarily due to a significant gap in data quality for supervised fine-tuning (SF…
cs.CV2026
PresentBench: A Fine-Grained Rubric-Based Benchmark for Slide Generation
Xin-Sheng Chen, Jiayu Zhu, Pei-lin Li +3
Slides serve as a critical medium for conveying information in presentation-oriented scenarios such as academia, education, and business. Despite their importance, creating high-qu…
cs.CV2025
RBench-V: A Primary Assessment for Visual Reasoning Models with Multi-modal Outputs
Meng-Hao Guo, Xuanyu Chu, Qianrui Yang +12
The rapid advancement of native multi-modal models and omni-models, exemplified by GPT-4o, Gemini, and o3, with their capability to process and generate content across modalities s…