3 papers
cs.CV2026
FREAK: A Fine-grained Hallucination Evaluation Benchmark for Advanced MLLMs
Zhihan Yin, Jianxin Liang, Yueqian Wang +3
Multimodal Large Language Models (MLLMs) suffer from hallucinations. Existing hallucination evaluation benchmarks are often limited by over-simplified tasks leading to saturated me…
cs.LG2025
K-frames: Scene-Driven Any-k Keyframe Selection for long video understanding
Yifeng Yao, Yike Yun, Jing Wang +6
Multimodal Large Language Models (MLLMs) have demonstrated significant capabilities in image understanding, but long-video are constrained by context windows and computational cost…
cs.CV2024
Selective Visual Prompting in Vision Mamba
Yifeng Yao, Zichen Liu, Zhenyu Cui +2
Pre-trained Vision Mamba (Vim) models have demonstrated exceptional performance across various computer vision tasks in a computationally efficient manner, attributed to their uniq…