benchmark dataset 1hallucination detection 1motion hallucination 1video large language models 1video understanding 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.CV2026
MoHallBench: A Benchmark for Motion Hallucination in Video Large Language Models
Sihan Chen, Jiale Li, Jianghang Lin +1
The paper introduces MoHallBench, a large benchmark designed to evaluate and diagnose motion hallucination—incorrectly inferred human motions—in video large language models, coveri…
cs.CV2025
MIHBench: Benchmarking and Mitigating Multi-Image Hallucinations in Multimodal Large Language Models
Jiale Li, Mingrui Wu, Zixiang Jin +5
Despite growing interest in hallucination in Multimodal Large Language Models, existing studies primarily focus on single-image settings, leaving hallucination in multi-image scena…
cs.CV2025
ControlMLLM: Training-Free Visual Prompt Learning for Multimodal Large Language Models
Mingrui Wu, Xinyue Cai, Jiayi Ji +7
In this work, we propose a training-free method to inject visual prompts into Multimodal Large Language Models (MLLMs) through test-time optimization of a learnable latent variable…