4 papers
WildTableBench: Benchmarking Multimodal Foundation Models on Table Understanding In the Wild
Junzhe Huang, Xiaoxiao Sun, Yan Yang +6
Using multimodal foundation models to analyze table images is a high-value yet challenging application in consumer and enterprise scenarios. Despite its importance, current evaluat…
MA-Bench: Towards Fine-grained Micro-Action Understanding
Kun Li, Jihao Gu, Fei Wang +3
With the rapid development of Multimodal Large Language Models (MLLMs), their potential in Micro-Action understanding, a vital role in human emotion analysis, remains unexplored du…
Uncovering What, Why and How: A Comprehensive Benchmark for Causation Understanding of Video Anomaly
Hang Du, Sicheng Zhang, Binzhu Xie +16
Video anomaly understanding (VAU) aims to automatically comprehend unusual occurrences in videos, thereby enabling various applications such as traffic surveillance and industrial…
DocMSU: A Comprehensive Benchmark for Document-level Multimodal Sarcasm Understanding
Hang Du, Guoshun Nan, Sicheng Zhang +6
Multimodal Sarcasm Understanding (MSU) has a wide range of applications in the news field such as public opinion analysis and forgery detection. However, existing MSU benchmarks an…