2 citations · 4 across the 15 of their papers we have counts for
8 papers · 1 filter
Detector-Empowered Video Large Language Model for Efficient Spatio-Temporal Grounding
Shida Gao, Feng Xue, Xiangfeng Wang +8
Multimodal large language models (MLLMs) are rapidly expanding from general video understanding to finer-grained understanding such as spatio-temporal video grounding (STVG) and re…
MARS2 2025 Challenge on Multimodal Reasoning: Datasets, Methods, Results, Discussion, and Outlook
Peng Xu, Shengwu Xiong, Jiajun Zhang +125
This paper reviews the MARS2 2025 Challenge on Multimodal Reasoning. We aim to bring together different approaches in multimodal machine learning and LLMs via a large benchmark. We…
AdsQA: Towards Advertisement Video Understanding
Xinwei Long, Kai Tian, Peng Xu +10
Large language models (LLMs) have taken a great step towards AGI. Meanwhile, an increasing number of domain-specific problems such as math and programming boost these general-purpo…
ICM-Fusion: In-Context Meta-Optimized LoRA Fusion for Multi-Task Adaptation
Yihua Shao, Xiaofeng Lin, Xinwei Long +7
Enabling multi-task adaptation in pre-trained Low-Rank Adaptation (LoRA) models is crucial for enhancing their generalization capabilities. Most existing pre-trained LoRA fusion me…
EventVAD: Training-Free Event-Aware Video Anomaly Detection
Yihua Shao, Haojin He, Sijie Li +11
Video Anomaly Detection~(VAD) focuses on identifying anomalies within videos. Supervised methods require an amount of in-domain training data and often struggle to generalize to un…
MambaIC: State Space Models for High-Performance Learned Image Compression
Fanhu Zeng, Hao Tang, Yihua Shao +3
A high-performance image compression algorithm is crucial for real-time information transmission across numerous fields. Despite rapid progress in image compression, computational…