1 citations · 1 across the 3 of their papers we have counts for
7 papers
ChineseVideoBench: Benchmarking Multi-modal Large Models for Chinese Video Question Answering
Yuxiang Nie, Han Wang, Yongjie Ye +15
This paper introduces ChineseVideoBench, a pioneering benchmark specifically designed for evaluating Multimodal Large Language Models (MLLMs) in Chinese Video Question Answering. T…
SAIL-Embedding Technical Report: Omni-modal Embedding Foundation Model
Lin Lin, Jiefeng Long, Zhihe Wan +15
Multimodal embedding models aim to yield informative unified representations that empower diverse cross-modal tasks. Despite promising developments in the evolution from CLIP-based…
Boosting Multi-modal Keyphrase Prediction with Dynamic Chain-of-Thought in Vision-Language Models
Qihang Ma, Shengyu Li, Jie Tang +5
Multi-modal keyphrase prediction (MMKP) aims to advance beyond text-only methods by incorporating multiple modalities of input information to produce a set of conclusive phrases. T…
SAIL-VL2 Technical Report
Weijie Yin, Yongjie Ye, Fangxun Shu +11
We introduce SAIL-VL2, an open-suite vision-language foundation model (LVM) for comprehensive multimodal understanding and reasoning. As the successor to SAIL-VL, SAIL-VL2 achieves…
MEML-GRPO: Heterogeneous Multi-Expert Mutual Learning for RLVR Advancement
Weitao Jia, Jinghui Lu, Haiyang Yu +17
Recent advances demonstrate that reinforcement learning with verifiable rewards (RLVR) significantly enhances the reasoning capabilities of large language models (LLMs). However, s…
SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement
Weijie Yin, Dingkang Yang, Hongyuan Dong +5
Vision Transformers (ViTs) are essential as foundation backbones in establishing the visual comprehension capabilities of Multimodal Large Language Models (MLLMs). Although most Vi…